use of interferon-γ release assays (igras) in tuberculosis control … · and igra positivity...

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USE OF INTERFERON-γ RELEASE ASSAYS (IGRAs) IN TUBERCULOSIS CONTROL

IN LOW- AND MIDDLE-INCOME SETTINGS

EXPERT GROUP MEETING REPORT 20-21 JULY 2010

This report contains the collective views of an international group of experts, and does not necessarily represent the decisions or the stated policy of the World Health Organization. Mention

of a technology does not imply endorsement of any specific commercial product.

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Executive summary

Background Research over the past decade has resulted in the development of two commercial interferon-gamma release assays (IGRAs). Both assays work on the principle that the T-cells of an individual who have acquired TB infection will respond to re-stimulation with M. tuberculosis-specific antigens by secreting interferon-gamma. The QuantiFERON-TB Gold (QFT-G, Cellestis, Australia) and the newer generation QuantiFERON-TB Gold In-Tube (QFT-GIT, Cellestis, Australia) are whole-blood based enzyme-linked immunosorbent assays

(ELISA) measuring the amount of IFN- produced in response to three M. tuberculosis antigens (QFT-G: ESAT-6 and CFP-10; QFT-GIT: ESAT-6, CFP-10 and TB7.7). In contrast, the enzyme-linked immunospot (ELISPOT)-based T-SPOT.TB (Oxford Immunotec) measures the number of peripheral mononuclear cells that

produce INF- after stimulation with ESAT-6 and CFP-10. In recent years, IGRAs have become widely endorsed in high-income countries for diagnosis of latent TB infection (LTBI) and several guidelines (albeit equivocal) on their use have been issued. Currently, there are no guidelines for their use in high TB- and HIV-burden settings, typically found in low-and middle-income countries, where IGRA use are being marketed and promoted, especially in the private sector. Systematic reviews have suggested that IGRA performance differs in high- versus low TB and HIV incidence settings, with relatively lower sensitivity in high-burden settings. The majority of IGRA studies have been performed in high-income countries and mere extrapolation to low- and middle-income settings with high background TB infection rates is not appropriate. The WHO Stop TB Department has therefore commissioned systematic reviews on the use of IGRAs in low- and middle-income settings, in pre-defined target groups, with funding support from the UNICEF/UNDP/World Bank/WHO Special Programme for Research and Training in Tropical Diseases (TDR) and TREAT-TB/The Union. The target groups and major findings are briefly summarised below. Summary of results Use of IGRAs in diagnosis of active TB: IGRAs were explicitly designed to replace the TST in diagnosis of LTBI, and were not intended for diagnosis of active TB. Because IGRAs (like the TST) cannot distinguish LTBI from active TB, these tests are expected to have poor specificity for active TB in high-burden settings due to a high background prevalence of LTBI. Nineteen studies simultaneously estimating sensitivity and specificity among 2,067 TB suspects demonstrated a pooled sensitivity of 83% (95% CI 70% - 91%) and pooled specificity of 58% (95% CI 42% - 73%) for T-SPOT (8 studies), and a pooled sensitivity of 73% (95% CI 61% - 82%) and pooled specificity of 49% (95% CI 40% - 58%) for QFT-GIT (11 studies). There was no consistent evidence that either IGRA was more sensitive than the TST for diagnosis of active TB diagnosis. Two studies evaluated the incremental value of IGRAs and found no meaningful contribution of IGRAs for diagnosis of active TB beyond readily available patient data and conventional microbiological tests. Expert Group consensus: The quality of evidence for use of IGRAS in diagnosis of active TB was low and it is recommended that these tests should not be used as a replacement for conventional microbiological diagnosis of pulmonary and extra-pulmonary TB in low- and middle-income countries (strong recommendation). The Expert Group also noted that current evidence did not support the use of IGRAs as part of the diagnostic workup of adults suspected of active TB in low-and middle-income countries, irrespective of HIV status. This recommendation places a high value on avoiding the consequences of unnecessary treatment (high false-positives) given the low specificity of IGRAs in these settings. Use of IGRAs in children: Only two small studies were identified which prospectively estimated incidence of active TB in children who had been tested with QFT. Conflicting results were reported. When the reference standard for LTBI was exposure, all three tests (TST, QFT and T-SPOT) seemed to be associated with the

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level of exposure (categorised either dichotomously or by an exposure gradient); however, methodological inconsistencies between the studies regarding the selection and definition of reference standards for active TB and exposure limited the comparability of studies and results. Estimates of association were very similar, suggesting no difference in performance between TST and IGRAs for diagnosis of LTBI and active TB in children. Expert Group consensus: The quality of evidence for use of IGRAS in children was very low and it is recommended that these tests should not be used as an alternative to TST in paediatric TB in low and middle-income countries for the diagnosis of latent TB infection, or as an alternative to TST in the workup of a diagnosis of active TB disease in children, irrespective of HIV status (strong recommendation). The Expert Group also notes that there may be additional harms associated with blood collection in children and that issues such as acceptability and cost have not been adequately addressed in any studies. Use of IGRAs in HIV-infected individuals: 36 studies were identified that included 5,400 HIV-infected individuals. In persons with active TB (used as a surrogate reference standard for LTBI), pooled sensitivity estimates were higher for TSPOT (72%, 95% CI 62% - 81%, 8 studies) than for QFT-GIT (61%, 95% CI 41% - 75%, 8 studies). Large prospective cohort studies have established that persons with a positive TST have a 1.4 to 1.7-fold higher rate of active TB within one year compared to persons with a negative TST result. Three studies evaluating the predictive value of IGRAs in HIV-infected individuals showed that IGRAs have poor positive predictive value but high negative predictive value for active TB. While these results suggest that a negative IGRA result is reassuring (no person with a negative IGRA result developed culture-positive TB), the studies had serious limitations, including small sample sizes with short-duration of follow-up and differential evaluation and/or follow-up of persons with positive and negative IGRA results. Neither IGRA was consistently more sensitive than TST in head-to-head comparisons, and the impact of advance immunosuppression on IGRA validity remains unclear: Two studies reported TST and IGRA data stratified by CD4 count. In one study, the proportion of positive results among those with CD4 cell count <200 decreased by 27% (95% CI -61, 8) with TSPOT and 35% (95% CI -59, -11) with TST. In the other study, the proportion of positive results among those with CD4 cell count <200 decreased by 31% (95% CI (-53, -9) with TSPOT and increased by 15% (95% CI (-11, 41) with TST. All tests therefore seem to be affected by CD4+ cell count, and additional studies from low/middle income countries are needed. Expert Group consensus: The quality of evidence for use of IGRAS in individuals living with HIV infection was very low and recommended that these tests should not be used as a replacement for TST for the assessment of LTBI (strong recommendation). This recommendation also applies to HIV-positive children based on the generalisation of data from adults. Use of IGRAs in health care worker (HCW) screening: Limited data was available on the utility of screening HCWs for LTBI in high incidence countries. Three cross-sectional studies were evaluated comparing IGRA and TST performance in HCWs in three countries, although TST was only performed in two of these. TST and IGRA positivity rates were high in HCWs, ranging from 40% to 66%. IGRA positivity was slightly lower than TST positivity in the two studies comparing TST and IGRAs; however, the difference in estimated prevalence was significant in one study only. Serial testing data, evidence on the predictive value of IGRAs in HCWs, as well as reproducibility data are still absent for high-incidence settings and limited even in low-incidence settings. Expert Group consensus: The quality of evidence for use of IGRAS for screening of health care workers in low- and middle-income countries was very low and it is recommended that these tests should not be used in health care worker screening programmes (strong recommendation). The Expert Group also noted the lack of WHO policy on using the TST in health care worker screening programmes. Use of IGRAs in contact screening and outbreak investigations: 16 studies (14 original manuscripts and 2 unpublished studies) were identified which evaluated IGRAs in contact screening and outbreak investigations in low- and middle income countries. Seventy-five percent (12/16) of contact studies included children in their study populations. The majority of studies were cross-sectional and looked at concordance between TST and IGRAs. Due to significant heterogeneity in study designs and outcomes

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assessed in each study, it was not possible to pool the data. The majority of studies showed comparable LTBI prevalence by TST or IGRA in contacts and only 4 studies reported a statistically significant difference between positivity rates estimated by TST, SPOT.TB or QFT. The most commonly observed discordance was of the TST-positive/IGRA-negative type. Both IGRAs and the TST seemed to show positive associations with higher levels of exposure in cross-sectional studies, but the strength of the association (ie. adjusted odds ratio) varied across studies. Results indicated that concordance between TST and IGRAs ranged widely, with only moderate agreement. In high-income settings, IGRAs appear to be dynamic and are associated with conversions and reversions which has impact for serial testing of contacts; however no data exists for LMICs. Expert Group consensus: The quality of evidence for use of IGRAS for LTBI screening in contact and outbreak investigations was very low and it is recommended that these tests should not be used as a replacement for TST, neither in adults nor children investigated as close contacts of patients with confirmed active TB (strong recommendation). Predictive value of IGRAs: Three studies provided incidence rate ratios (IRR) of TB stratified by IGRA as well as TST status at baseline. The association with subsequent incident TB in test-positive individuals compared to test-negatives appeared higher for IGRA than for TST; however, this was not statistically significant (IGRA: IRR=3.24; 95CI 0.62-5.85; I2=0%; p=0.90; TST: IRR=2.28; 95CI 0.83-3.73); The Expert Group also noted that both IGRAs and TST seemed to show positive associations between exposure gradient and test results but with variability in the strength of the association across populations irrespective of BCG vaccination. No statistically significant increase in incidence rates of TB in IGRA- positives compared to IGRA-negatives was observed and the vast majority of individuals (>95%) with a positive IGRA result did not progress to active TB disease during follow-up. Both IGRAs and the TST appeared to have only modest predictive value and did not help identify those who are at highest risk of progression to disease. The predictive value for serial testing could not be assessed as all three studies performed single time-point IGRA testing. Patient relevant outcomes based on sensitivity and specificity appeared comparable between IGRAs and the TST. Expert Group consensus: The quality of evidence for the predictive value of IGRAS was very low and it is recommended that these assays should not be used to identify individuals at risk of active TB disease in low- and middle-income countries (strong recommendation).

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Contents

1. BACKGROUND .................................................................................................................................................... 1

2. EVIDENCE BASE .................................................................................................................................................. 3

2.1 EVIDENCE SYNTHESIS ............................................................................................................................................... 3

2.2 SYSTEMATIC REVIEWS AND META-ANALYSES ................................................................................................................ 4

2.3 GRADE EVALUATION .............................................................................................................................................. 6

2.4 MEETING PROCEDURAL ISSUES .................................................................................................................................. 7

3. RESULTS ............................................................................................................................................................. 8

3.1 USE OF IGRAS IN DIAGNOSIS OF ACTIVE TB ................................................................................................................. 8

3.1.1 Objectives, reference standards and outcomes ............................................................................................ 8

3.1.2 Search results ................................................................................................................................................ 9

3.1.3 Data analysis ................................................................................................................................................. 9

3.1.4 Study characteristics ................................................................................................................................... 10

3.1.5 Study quality ............................................................................................................................................... 10

3.1.6 Sensitivity and specificity estimation among TB suspects........................................................................... 10

3.1.7 Proportion of indeterminate IGRA results ................................................................................................... 17

3.1.8 Incremental value of IGRAs for active TB .................................................................................................... 18

3.1.9 Summary of findings and GRADE evidence profiles .................................................................................... 20

3.1.10 Strengths and limitations of the evidence base .......................................................................................... 21

3.1.11 Final recommendations............................................................................................................................... 21

3.2 USE OF IGRAS IN CHILDREN ................................................................................................................................... 29

3.2.1 Objectives, reference standards and outcomes .......................................................................................... 29

3.2.2 Data analysis ............................................................................................................................................... 31

3.2.3 Search results .............................................................................................................................................. 32


3.2.5 Study quality ............................................................................................................................................... 33

3.2.6 Test failure and indeterminate results across studies and populations ...................................................... 34

3.2.7 Studies assessing incident TB ...................................................................................................................... 35

3.2.8 Studies assessing exposure ......................................................................................................................... 35

3.2.9 Studies assessing active TB ......................................................................................................................... 39



3.2.12 Final recommendations............................................................................................................................... 48

3.3 USE OF IGRAS FOR THE DIAGNOSIS OF LTBI IN HIV-INFECTED INDIVIDUALS..................................................................... 60


3.3.2 Search results .............................................................................................................................................. 60


3.3.4 Study quality ............................................................................................................................................... 61

3.3.5 Risk of progression to active TB .................................................................................................................. 61

3.3.6 Sensitivity in culture-confirmed active TB patients ..................................................................................... 62

3.3.7 Agreement between IGRA and TST results .................................................................................................. 63

3.3.8 Indeterminate IGRA results ......................................................................................................................... 64

3.3.9 Impact of immunosuppression .................................................................................................................... 65


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3.3.11 Research gaps ............................................................................................................................................. 68


3.3.13 Final Recommendations .............................................................................................................................. 68

3.4 USE OF IGRAS FOR SCREENING OF HEALTH CARE WORKERS........................................................................................... 73


3.4.2 Search results .............................................................................................................................................. 73


3.4.4 Study quality ............................................................................................................................................... 74

3.4.5 IGRA vs. TST positivity rates in high-incidence countries ............................................................................ 74

3.4.6 IGRA conversion and reversion rates in longitudinal, serial testing ............................................................ 75

3.4.7 Association between occupational risk factors and test results in HCWs ................................................... 76

3.4.8 Cost-effectiveness of IGRAs in HCW screening ............................................................................................ 76


3.4.10 Research gaps ............................................................................................................................................. 76



3.5 USE OF IGRAS IN CONTACT SCREENING AND OUTBREAK INVESTIGATIONS ........................................................................ 83


3.5.2 Search results .............................................................................................................................................. 83

3.5.3 Data analysis ............................................................................................................................................... 84


3.5.5 Study quality ............................................................................................................................................... 84

3.5.6 Agreement between IGRA and TST Results ................................................................................................. 85

3.5.7. Correlation between test positivity and exposure....................................................................................... 87

3.5.8 Concordance between test results in longitudinal contact studies ............................................................. 95

3.5.9. Indeterminate IGRA results ......................................................................................................................... 98

3.5.10 Strengths & limitations of the evidence base.............................................................................................. 98



3.6 THE PREDICTIVE VALUE OF IGRAS FOR INCIDENT ACTIVE TB ........................................................................................ 102

3.6.1 Objectives, reference standards and outcomes ........................................................................................ 102

3.6.2 Search results ............................................................................................................................................ 103

3.6.3 Data analysis ............................................................................................................................................. 103

3.6.4 Study characteristics ................................................................................................................................. 103

3.6.5 Study quality ............................................................................................................................................. 103

3.6.6 Incidence rates of TB during follow-up ..................................................................................................... 104

3.6.7 The association between IGRA and incident active TB ............................................................................. 106

3.6.8 The predictive value of IGRA compared with TST ..................................................................................... 106

3.6.9 The influence of discordant- concordant TST/IGRA pairs at baseline on subsequent TB rates ................. 108

3.6.10 Gradient between rates of TB and quantitative IGRA levels ..................................................................... 109

3.6.11 Patient relevant outcomes ........................................................................................................................ 109

3.6.12 The predictive value of serial testing ........................................................................................................ 110

3.6.13 Summary of findings and GRADE evidence profiles .................................................................................. 110

3.6.14 Final Recommendations ............................................................................................................................ 110

3.7 OPERATIONAL ASPECTS ON THE USE OF IGRAS IN HIGH TB BURDEN COUNTRIES ............................................................. 117

ANNEX 1. MEETING PARTICIPANTS ..................................................................................................................................... 119

ANNEX 2. DECLARATIONS OF INTEREST ................................................................................................................................ 122

ANNEX 3. SELECTION OF STUDIES EVALUATING THE USE OF IGRA IN THE DIAGNOSIS OF ACTIVE TB .................................................. 123

ANNEX 4. SELECTION OF STUDIES EVALUATING THE USE OF IGRAS IN CHILDREN .......................................................................... 135

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ANNEX 5. SELECTION OF STUDIES EVALUATING THE USE OF IGRAS FOR THE DIAGNOSIS OF LTBI IN HIV-POSITIVE INDIVIDUALS ............. 141

ANNEX 6. SELECTION OF STUDIES EVALUATING THE USE OF IGRAS FOR TUBERCULOSIS SCREENING OF HEALTH CARE WORKERS .............. 152

ANNEX 7. SELECTION OF STUDIES EVALUATING THE USE OF IGRAS LTBI SCREENING IN CONTACT AND OUTBREAK INVESTIGATIONS ........ 157

ANNEX 8. SELECTION OF STUDIES EVALUATING THE PREDICTIVE VALUE OF IGRAS FOR INCIDENT ACTIVE TB DISEASE IN LOW, MIDDLE AND

HIGH INCOME COUNTRIES .................................................................................................................................................. 165

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List of Figures

FIGURE 1. HIERARCHY OF REFERENCE STANDARDS USED TO ASSESS THE EVIDENCE BASE .................................................................. 4

FIGURE 2. ASSESSMENT OF STUDY QUALITY USING THE QUADAS TOOL .................................................................................... 10

FIGURE 3A-3C. HIERARCHICAL SUMMARY RECEIVER OPERATING CHARACTERISTICS (HSROC) PLOT OF STUDIES THAT REPORTED BOTH

SENSITIVITY AND SPECIFICITY IN ACTIVE TB SUSPECTS ............................................................................................................ 11

FIGURE 4. SENSITIVITY OF QUANTIFERON-TB GOLD IN-TUBE AND T-SPOT.TB IN HIV-POSITIVE PERSONS WITH CONFIRMED ACTIVE

TUBERCULOSIS IN LOW- AND MIDDLE-INCOME COUNTRIES ..................................................................................................... 12

FIGURE 5. SENSITIVITY OF QUANTIFERON-TB GOLD IN-TUBE AND T-SPOT.TB IN HIV-NEGATIVE PERSONS WITH CONFIRMED ACTIVE

TUBERCULOSIS IN LOW- AND MIDDLE-INCOME COUNTRIES ..................................................................................................... 13

FIGURE 6. PERCENT SENSITIVITY DIFFERENCE BETWEEN IGRA AND TST RESULTS......................................................................... 16

FIGURE 7. PROPORTION OF INDETERMINATE IGRA RESULTS AMONG HIV-NEGATIVE SUBJECTS IN LOW- AND MIDDLE-INCOME COUNTRIES

17

FIGURE 8. PROPORTION OF INDETERMINATE IGRA RESULTS AMONG HIV-POSITIVE SUBJECTS IN LOW- AND MIDDLE-INCOME COUNTRIES

18

FIGURE 9. RECEIVER OPERATING CHARACTERISTIC (ROC) CURVES FOR BASELINE CLINICAL PREDICTION MODEL WITH AND WITHOUT

ADDITION OF IGRA (UNPUBLISHED) .................................................................................................................................. 19

FIGURE 10. RECEIVER OPERATING CHARACTERISTIC (ROC) CURVES FOR BASELINE CLINICAL PREDICTION MODEL WITH AND WITHOUT

ADDITION OF QUANTIFERON-GOLD IN-TUBE AND TUBERCULIN SKIN TEST (UNPUBLISHED) ......................................................... 20

FIGURE 11. METHODOLOGICAL QUALITY: EXPOSURE STUDIES ................................................................................................... 34

FIGURE 12: METHODOLOGICAL QUALITY: STUDIES ASSESSING ACTIVE TB .................................................................................... 34

FIGURE 13. POOLED ODDS RATIOS (95% CIS): CONCORDANCE OF TEST WITH DICHOTOMOUS EXPOSURE.......................................... 36

FIGURE 14. POOLED ESTIMATES: CORRELATION OF TESTS WITH EXPOSURE GRADIENTS .................................................................. 38

FIGURE 15. REGRESSION SLOPES BY EXPOSURE GRADIENT......................................................................................................... 38

FIGURE 16. FOREST PLOTS FOR TST SENSITIVITY AND SPECIFICITY IN ACTIVE TB, SEPARATED BY WORLD BANK INCOME INDEX ............... 44

FIGURE 17. FOREST PLOTS FOR QUANTIFERON SENSITIVITY AND SPECIFICITY IN ACTIVE TB, SEPARATED BY WORLD BANK INCOME INDEX . 45

FIGURE 18. FOREST PLOTS FOR T-SPOT SENSITIVITY AND SPECIFICITY IN ACTIVE TB, SEPARATED BY WORLD BANK INCOME INDEX ......... 46

FIGURE 19. SENSITIVITY OF IGRAS IN HIV-POSITIVE INDIVIDUALS WITH CONFIRMED ACTIVE TB ...................................................... 63

FIGURE 20. PERCENT CONCORDANCE BETWEEN IGRA AND TST RESULTS .................................................................................... 64

FIGURE 21. PROPORTION OF INDETERMINATE IGRA RESULTS IN HIV-INFECTED PERSONS SCREENED FOR LTBI ................................... 65

FIGURE 22. IMPACT OF IMMUNOSUPPRESSION ON IGRA RESULTS ............................................................................................. 66

FIGURE 23. LTBI AND TST PREVALENCE IN LOW- AND MIDDLE-INCOME SETTINGS ........................................................................ 75

FIGURE 24. STUDIES EVALUATING CONCORDANCE BETWEEN TST AND IGRAS .............................................................................. 86

FIGURE 25. SUMMARY DIFFERENCES IN PREVALENCE OF POSITIVE TESTS AGAINST PROPORTION BCG VACCINATED .............................. 87

FIGURE 26. ASSOCIATION BETWEEN TEST POSITIVITY AND TB EXPOSURE, AS A DICHOTOMOUS VARIABLE ........................................... 88

FIGURE 27A. ASSOCIATION BETWEEN TST POSITIVITY AND EXPOSURE GRADIENT ............................................................................ 93

FIGURE 27B. ASSOCIATION BETWEEN IGRA POSITIVITY AND EXPOSURE GRADIENT .......................................................................... 93

FIGURE 28. CRUDE TB INCIDENCE RATES STRATIFIED BY IGRA STATUS ...................................................................................... 105

FIGURE 29. CRUDE, UNADJUSTED TB INCIDENCE RATE RATIOS FOR IGRA-POSITIVES VS. IGRA-NEGATIVES ...................................... 106

FIGURE 30. CRUDE, UNADJUSTED INCIDENCE RATE RATIOS FOR IGRAS COMPARED TO THE TST ..................................................... 107

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List of Tables

TABLE 1. QUADAS .......................................................................................................................................................... 5

TABLE 2. HEAD-TO-HEAD COMPARISON OF SENSITIVITY OF T-SPOT.TB VERSUS QUANTIFERON-TB GOLD IN-TUBE AMONG ACTIVE TB

SUSPECTS ......................................................................................................................................................... 14

TABLE 3. GRADE EVIDENCE PROFILE:1 DIAGNOSTIC ACCURACY OF CURRENTLY AVAILABLE COMMERCIAL INTERFERON-GAMMA RELEASE

ASSAYS (QUANTIFERON-TB GOLD IN-TUBE [QFT-GIT], CELLESTIS, AUSTRALIA AND T-SPOT.TB [T-SPOT], OXFORD

IMMUNOTEC, UNITED KINGDOM) FOR EVALUATION OF PATIENTS WITH PULMONARY TB IN LOW- AND MIDDLE-INCOME

COUNTRIES ....................................................................................................................................................... 22

TABLE 4. GRADE SUMMARY OF FINDINGS – ROLE OF IGRAS FOR EVALUATION OF PATIENTS WITH PULMONARY TB IN LOW- AND MIDDLE-

INCOME COUNTRIES ............................................................................................................................................ 25

TABLE 5: STUDIES WITH DICHOTOMOUS EXPRESSION OF EXPOSURE INCLUDED IN ANALYSIS OF TEST PERFORMANCE FOR LTBI, SORTED BY

WORLD BANK INCOME INDEX ............................................................................................................................... 35

TABLE 6. STUDIES WITH EXPOSURE GRADIENTS INCLUDED IN ANALYSIS OF TEST PERFORMANCE FOR LTBI, SORTED BY WORLD BANK

INCOME INDEX ................................................................................................................................................... 37

TABLE 7. STUDIES INCLUDED IN ANALYSIS OF TEST PERFORMANCE IN TB DISEASE, SORTED BY WORLD BANK INCOME INDEX ................. 40

TABLE 8. DIAGNOSTIC ACCURACY OF TST, QFT AND T-SPOT IN ACTIVE DISEASE IN CHILDREN, INCLUDING ALL ACCEPTABLE DEFINITIONS

OF TB AND ALL COUNTRIES (HIC AND LMIC) .......................................................................................................... 41

TABLE 9. GRADE EVIDENCE PROFILE: THE PERFORMANCE OF IGRAS FOR THE DIAGNOSIS OF LATENT TUBERCULOSIS INFECTION IN

CHILDREN IN LMIC ............................................................................................................................................. 50

TABLE 10. GRADE SUMMARY OF FINDINGS – IGRAS FOR LTBI IN CHILDREN ............................................................................... 52

TABLE 11. GRADE EVIDENCE PROFILE: THE DIAGNOSTIC ACCURACY OF IGRAS FOR THE DIAGNOSIS OF ACTIVE TUBERCULOSIS IN CHILDREN

IN LMIC ........................................................................................................................................................... 53

TABLE 12. GRADE SUMMARY OF FINDINGS – IGRAS FOR THE DIAGNOSIS OF ACTIVE TB IN CHILDREN .............................................. 56

TABLE 13. RISK OF ACTIVE TUBERCULOSIS IN HIV-INFECTED INDIVIDUALS, STRATIFIED BY IGRA RESULT ............................................. 62

TABLE 14. GRADE EVIDENCE PROFILE: THE ROLE OF IGRAS IN THE DIAGNOSIS OF LATENT TUBERCULOSIS INFECTION IN HIV-INFECTED

INDIVIDUALS...................................................................................................................................................... 70

TABLE 15. GRADE SUMMARY OF FINDINGS – ROLE OF IGRAS FOR DIAGNOSIS OF LTBI IN HIV INFECTED INDIVIDUALS ....................... 72

TABLE 16. GRADE EVIDENCE PROFILE: INTERFERON-Γ RELEASE ASSAYS FOR TUBERCULOSIS SCREENING OF HEALTHCARE WORKERS IN LOW

AND MIDDLE INCOME COUNTRIES .......................................................................................................................... 78

TABLE 17. GRADE SUMMARY OF FINDINGS – IGRAS FOR TUBERCULOSIS SCREENING OF HEALTHCARE WORKERS IN LOW AND MIDDLE INCOME

COUNTRIES ....................................................................................................................................................... 81

TABLE 18. RESULTS FROM STUDIES USING EXPOSURE GRADIENTS ............................................................................................... 90

TABLE 19. TST AND QFT CONVERSIONS IN CONTACT STUDIES IN LOW- AND MIDDLE-INCOME COUNTRIES .......................................... 97

TABLE 20. GRADE EVIDENCE PROFILE: PERFORMANCE OF IGRAS FOR THE DIAGNOSIS OF LTBI IN CONTACTS OF ACTIVE TB IN LOW-AND

MIDDLE-INCOME COUNTRIES. ............................................................................................................................... 99

TABLE 21. DISCORDANT-CONCORDANT TST/IGRA PAIRS AND INCIDENCE RATES OF TB ............................................................... 109

TABLE 22. GRADE EVIDENCE PROFILE: PREDICTIVE VALUE OF COMMERCIAL IGRA FOR INCIDENT ACTIVE TB IN LOW AND MIDDLE-INCOME

COUNTRIES ..................................................................................................................................................... 111

TABLE 23. GRADE SUMMARY OF FINDINGS: PREDICTIVE VALUE OF COMMERCIAL IGRA FOR INCIDENT ACTIVE TB IN LOW AND MIDDLE-

INCOME COUNTRIES ......................................................................................................................................... 113

Use of IGRAs in diagnosis of active TB

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USE OF INTERFERON-γ RELEASE ASSAYS (IGRAs) IN TUBERCULOSIS CONTROL IN LOW- AND MIDDLE-INCOME SETTINGS

1. BACKGROUND

Tuberculosis (TB) continues to have a significant health impact worldwide, with one third of the world’s

population estimated to be infected with Mycobacterium tuberculosis, resulting in so-called latent TB

infection (LTBI). Until recently, the tuberculin skin test (TST) was the only tool available for LTBI diagnosis.

The TST involves intradermal injection of purified protein derivative (PPD), a crude mixture of

mycobacterial antigens, which stimulates a delayed type hypersensitivity response and causes induration at

the injection site within 48 to 72 hours.

The identification of genes in the Mycobacterium tuberculosis genome that are absent from M. bovis BCG

and most nontuberculous mycobacteria has supported the development of more specific and sensitive

tests for detection of M. tuberculosis. M. bovis BCG has 16-gene deletions including the region of difference

1 (RD-1) that encodes for early secretory antigen target-6 (ESAT-6) and culture filtrate protein 10 (CFP-

10).1,2 24, 26 ESAT-6 and CFP-10 are strong targets of the cellular immune response in patients with M.

tuberculosis infection.3,4 27, 28 In such persons, sensitized memory/effector T cells produce interferon-

gamma (IFN-) in response to these M. tuberculosis antigens, allowing a biologic basis for T-cell-based tests

such interferon-gamma release assays (IGRAs).

Research over the past decade has resulted in the development of two commercial IGRAs. Both assays

work on the principle that the T-cells of an individual who have acquired TB infection will respond to re-

stimulation with M. tuberculosis-specific antigens by secreting interferon-gamma. The QuantiFERON-TB

Gold (QFT-G, Cellestis, Australia) and the newer version QuantiFERON-TB Gold In-Tube (QFT-GIT, Cellestis,

Australia) are whole-blood based enzyme-linked immunosorbent assays (ELISA) measuring the amount of

IFN- produced in response to specific M. tuberculosis antigens (QFT-G: ESAT-6 and CFP-10, QFT-GIT: ESAT-

&, CFP-10, TB7.7). In contrast, the enzyme-linked immunospot (ELISPOT)-based T-SPOT.TB (Oxford

Immunotec, UK) measures the number of peripheral mononuclear cells that produce INF- after stimulation

with ESAT-6 and CFP-10.

Both IGRAs and the TST are surrogate markers of M. tuberculosis infection, indicating a cellular immune response to recent or remote sensitization with M. tuberculosis. Currently, there is no gold standard for the detection of M. tuberculosis infection, and neither the TST nor IGRAs can distinguish TB infection from active TB disease. Although routinely used, the TST has limited sensitivity and specificity. Factors related to the host, test administration and/or reading may diminish TST reactivity resulting in false-negative reactions and decreased TST sensitivity. Important factors associated with reduced TST sensitivity include malnutrition, young age, severe TB disease, HIV-related impaired cellular immunity, and other forms of immune suppression. Several factors are associated with decreased TST specificity and false-positive reactions including antigens shared between M. tuberculosis purified protein derivative (PPD), non-tuberculous mycobacteria (NTM) and BCG vaccine. Additionally, completing the TST requires two health care visits and measurement of reaction size is subjective, with documented poor inter-reader reliability. Nevertheless, the TST is the only test for which the risk of developing active TB in persons with a positive result has been well-defined.

IGRAs are the first new diagnostic test for latent tuberculosis infection (LTBI) in over 100 years. In previous

systematic reviews it has been shown that, in low TB incidence settings, IGRAs have higher specificity than

the TST, better correlation with surrogate measures of M. tuberculosis exposure, and less cross reactivity


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with the BCG vaccine. IGRAs do, however, require fairly sophisticated laboratory infrastructure and

technical expertise, and are costly.

In recent years, IGRAs have become widely endorsed in high-income countries for diagnosis of LTBI and

several guidelines (albeit equivocal) on their use have been issued. Currently, there are no guidelines for

their use in high TB- and HIV-burden settings, typically found in low-and middle-income countries, where

IGRA use are being marketed and promoted, especially in the private sector. While strong evidence has

emerged that IGRAs are unaffected by BCG vaccination, systematic reviews have suggested that IGRA

performance differs in high- versus low TB and HIV incidence settings, with relatively lower sensitivity in

high-burden settings. The WHO Stop TB department has therefore commissioned systematic reviews on

the use of IGRAs in low- and middle-income settings, in pre-defined target groups, with funding support

from the UNICEF/UNDP/World Bank/WHO Special Programme for Research and Training in Tropical

Diseases (TDR) and TREAT-TB/The Union. The target groups and the rationale for their selection are briefly

summarized below:

Use of IGRAs in diagnosis of active TB: IGRAs were explicitly designed to replace the TST in diagnosis of

LTBI, and were not intended for active TB. Diagnosis and treatment of LTBI remains limited in scope in most

low- and middle-income countries, where detection and management of active TB is the highest priority for

national TB programmes. Because IGRAs (like the TST) cannot distinguish LTBI from active TB, these tests

can be expected to have poor specificity for active TB in high-burden settings due to a high background

prevalence of LTBI. Additional differences in patient spectrum, such as anergy due to advanced disease,

malnutrition, and HIV-associated immune suppression, or characteristics of the setting, such as laboratory

procedures and infrastructure, may also contribute to a lower performance of IGRAs observed in these

settings. Yet, especially private sector laboratories in high-burden, countries increasingly employ IGRAs for

active TB diagnosis, and many investigators continue to recommend the use of IGRAs either as individual or

adjunct trests for diagnosis of active TB.

Use of IGRAs in children: Children carry an estimated 15% of the global burden of TB disease. More than

60% of children <5 years of age diagnosed with TB in high-burden countries have documented household

exposure, while community exposure increases with age. Children therefore constitute an increasing TB

infection reservoir that are at high risk of primary disease progression in the absence of isoniazid

preventive therapy (IPT) and who may also develop subsequent adult reactivation disease. In addition,

young children have a disproportionately high risk of early progression to primary disease and developing

severe forms of disease (eg. TB meningitis or miliary TB), often exacerbated by HIV infection (with increased

mortality), especially in Sub-Saharan Africa. Limited public health resources are available to identify and

manage the increasingly large pool of TB-infected children. In addition, the diagnosis of paucibacillary

disease in children is complicated by the difficulty of bacteriological confirmation and often relies on a

composite of risk factors, clinical and radiological findings, all of which are rather unspecific. Diagnostic

algorithms for pediatric disease often include use of the TST, with a positive TST considered supportive of

the diagnosis. Possible improved performance of IGRAs over TST in this context therefore needs to be

explored.

Use of IGRAs in HIV-infected individuals: TB has become the leading cause of death in persons with HIV and HIV is the most potent risk factor for progression from latent to active TB. Preventative therapy with isoniazid reduces the risk of active TB by up to 60%; however, the optimal test to identify HIV-infected individuals who could benefit from IPT remains uncertain. Importantly, there is strong evidence that IPT reduces the risk of TB in persons with positive TST results (irrespective of HIV result); however, the TST is impaired in HIV infection, and severely compromised in individual with a low CD4 count. Data are urgently


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needed to evaluate the use of IGRAs to improve the identification of HIV-infected persons who could benefit from IPT, diagnosing LTBI rather than ruling out active TB (an important distinction in HIV-infected persons initiating IPT).

Use of IGRAs in health care worker (HCW) screening and contact investigations: TB poses a significant

occupational health problem and HCWs are at increased risk for exposure to TB and subsequent disease,

especially if co-infected with HIV. In many high-income countries, periodic screening of HCWs and contacts

of confirmed TB patients for LTBI is a routine component of TB control; however, contact and HCW

screening is often neglected in low- and middle-income settings. Traditionally, prevalence of LTBI and

incidence of new TB infection (i.e. conversion) among such individuals have been estimated using the TST.

IGRAs have emerged as an alternative, being ex-vivo blood-based tests that, in contrast to the TST, can be

repeated any number of times without sensitization or boosting. However, data are lacking on how to

interpret repeated (serial) IGRA testing results and studies have documented conversions and reversions

during serial testing. Several questions also remain about the usefulness of IGRAs to determine incidence of

new infections among HCWs and contacts, an issue critical for understanding of TB transmission,

nosocomial spread, and the impact of existing and new TB infection control interventions and strategies.

Predictive value of IGRAs: The clinical benefit of IGRAs, supported by data on the longitudinal predictive (prognostic) value of IGRA and their added value in the control of TB is currently unknown. In contrast, the predictive value of a positive TST has been well-defined, showing that TST reactivity is associated with an increased risk of active TB in subsequent years. Strong evidence from randomized trials has shown that IPT benefit is restricted to individuals with a positive TST (irrespective of HIV result), providing a relative risk reduction of around 60%. To demonstrate equivalent or superior clinical utility of IGRAS over TST, IGRAs would have to be subjected to similar evaluations and in various at-risk populations, especially in low-and middle-income countries with limited and often competing public health resources.

2. EVIDENCE BASE

2.1 Evidence synthesis

The systematic, structured, evidence-based process for TB diagnostic policy generation developed by WHO-

STB was followed: The first step constituted systematic reviews and meta-analysis of available data

(published and unpublished) using standard methods appropriate for diagnostic accuracy studies. The

second step involved the convening of an Expert Group to a) evaluate the strength of the evidence base; b)

recommend operational and logistical considerations for mainstreaming such methods/approaches into

national TB control programmes; and c) identify gaps to be addressed in future research. Based on the

Expert Group findings, the third and final step involves WHO policy guidance on the use of these

tools/approaches, presented to the WHO Strategic and Technical Advisory Group for TB (STAG-TB) for

consideration, and eventual dissemination to WHO Member States for implementation.

The Expert Group (Annex 1) consisted of researchers, clinicians, epidemiologists, end-users (programme

and laboratory representatives), community representatives and evidence synthesis experts. The Expert

Group meeting followed a structured agenda (Annex 1) and was co-chaired by WHO secretariat.

To comply with current standards for evidence assessment in formulation of policy recommendations, the

GRADE system (www.gradeworkinggroup.org ), adopted by WHO for all policy and guidelines development,

was used. The GRADE approach, assessing both the quality of evidence and strength of recommendations,

aims to provide a comprehensive and transparent approach for developing policy guidance. Started about

10 years ago to assess treatment interventions, the GRADE approach has recently been refined for

http://www.gradeworkinggroup.org/


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diagnostics;6 however, while the latter process shares the fundamental logic of recommendations for other

interventions (notably treatment), it also presents unique challenges, most often due to study limitations

related to a lack of data on patient-important outcomes and impact (see below).

Given the absence of studies evaluating patient-important outcomes among TB suspects randomized to

treatment based on IGRA results, reviews were focused on the diagnostic accuracy of IGRAs versus TST in

detecting LTBI or active TB.

2.2 Systematic reviews and meta-analyses

Systematic reviews were done following standard guidelines for systematic reviews and detailed protocols

with predefined questions relevant to the individual topics. Summaries of methodology followed for each

topic are given in the respective sections below. Detailed methodology is described in the individual

systematic review reports available at http://www.who.int/tb/laboratory/policy_statements.

Hierarchy of reference standards: Studies evaluating the performance of IGRAs are hampered by the lack

of an adequate gold standard to distinguish the presence or absence of LTBI. Since diagnostic accuracy for

LTBI could not be directly assessed, a hierarchy of reference standards was developed and agreed

beforehand with the systematic reviewers (Figure 1) that would evaluate the role of IGRAs depending on

the individual topic (i.e. not all systematic reviews necessarily used the hierarchy).

Primary outcomes were predefined for each systematic review as relevant, e.g. the predictive value of

IGRAs for development of active TB, the sensitivity of IGRAs in persons with culture-confirmed active TB (as

a surrogate reference standard for TB infection), and the correlation between IGRA and TST results.

In addition to primary outcomes, specific characteristics of IGRAs that could influence their overall utility

were evaluated where relevant, e.g. the proportion of indeterminate IGRA results (i.e. not interpretable

either due to high IFN-γ response in the negative control or low IFN-γ response in the positive control), the

impact of HIV-related immunosuppression (i.e. CD4+ cell count) on test performance where available, and

correlation of IGRA results with an exposure gradient (typically used in contact and outbreak

investigations).

Figure 1. Hierarchy of reference standards used to assess the evidence base


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Search methods: All studies evaluating IGRAs published through May 2010 were reviewed using predefined

data search strings. In addition to database searches, bibliographies of reviews and guidelines were

reviewed, citations of all included studies were screened, and experts in the field as well as IGRA

manufacturers were contacted to identify additional published, unpublished, and ongoing studies.

Pertinent information not reported in the original publication, from the primary authors of all studies

included, were requested and obtained by the systematic reviewers.

Study selection: Studies published in all languages and in all low- and middle-income countries that

evaluated the performance of the newest commercial, RD1 antigen-based IGRAs were reviewed per

individual topic. Excluded were: (1) studies that evaluated non-commercial (in-house) IGRAs, older

generation IGRAs (i.e., purified protein derivative [PPD]-based IGRAs) and IGRAs performed in specimens

other than blood; (2) studies focused on the effect of anti-TB treatment on IGRA response; (3) studies

including < 10 individuals; (4) studies reporting insufficient data to determine diagnostic accuracy

measures; and (5) conference abstracts, letters without original data, and reviews.

Assessment of study quality: Study quality was assessed by relevant standardised methods depending on

the topic. For primary outcomes focused on test accuracy, a subset of relevant criteria from QUADAS, a

validated tool for diagnostic accuracy studies, was used. For studies of the predictive value of IGRAs, quality

was appraised with a modified version of the Newcastle-Ottawa Scale (NOS) for longitudinal/cohort

studies.

Table 1. QUADAS

Conflicts of interest are a known concern in TB diagnostic studies; therefore, the systematic reviews added

a quality item about involvement of commercial test manufacturers in published studies and reported

whether IGRA manufacturers had any involvement with the design or conduct of each study, including

donation of test materials, provision of monetary support, work/financial relationships with study authors,

and participation in data analysis.

Outcome definitions: Explicit definitions for primary and secondary outcomes were defined in the original

systematic review protocols, pre-specified per individual topic and described in the individual sections

below.


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Data synthesis and meta-analysis: A standardised overall approach was specified a priori for each

systematic review to account for significant heterogeneity in results expected between studies. First, data

were synthesised separately for each commercial IGRA and by the World Bank country income

classification (low/middle income versus high income) as a surrogate for TB incidence. Second,

heterogeneity was visually assessed using forest plots, the variation in study results attributable to

heterogeneity was characterised (I-squared statistic), and statistically tested (chi-squared test). Third,

pooled estimates were calculated using random effects modelling, which provides more conservative

estimates than fixed effects modelling when heterogeneity is present.

For each individual study, all outcomes for which data were available were assessed. First, forest plots were

generated to display the individual study estimates and their 95% confidence intervals. Pooled estimates

were calculated when at least three studies were available in any sub-group and individual study results

summarised when less than four studies were available. Standard statistical packages were used for

analyses.

2.3 GRADE evaluation

Evaluation followed the GRADE system for grading quality of evidence and strength of recommendations

for diagnostic tests. The quality of evidence was graded by six criteria:

Study design

Cross-sectional: Random or consecutive selection of patients/specimens at risk (preferred);

Case-control: Selection of patients/specimens according to reference standard.

Risk of bias (as reflected by the QUADAS tool)

Compliance of studies with relevant independent quality assessment criteria (Table 1).

Directness

Presence of direct evidence of impact on patient-important outcomes and generalisability.

Inconsistency

Unexplained inconsistency in sensitivity or specificity estimates.

Imprecision

Wide confidence intervals for pooled sensitivity or specificity estimates.

Publication/reporting bias

Publications of research based on their nature and outcome, eg. studies showing poor performance not

being published, language bias, etc.

As called for by GRADE, the Expert Group also considered for each method/approach the strength of the

recommendation (strong or conditional/weak), based on a balance of effects (advantages weighed against

disadvantages), patient values and preferences, and costs.


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Given the absence of relevant data from the studies reviewed, assumed patient values and preferences

were assessed by test accuracy as a proxy measure, based on the relative importance/impact of false-

positive and false-negative results:

True positives: Benefit to patients from earliest diagnosis and treatment;

True negatives: Patients spared unnecessary treatment; benefit of reassurance and alternative diagnosis;

False positives: Likely patient anxiety and morbidity from additional testing, unnecessary treatment; may

halt further diagnostic evaluation;

False negatives: Increased risk of patient morbidity and mortality, and continued risk of community

transmission of TB.

2.4 Meeting procedural issues

The systematic review reports were made available to the Expert Group for scrutiny before the meeting.

As agreed, interchange by Expert Group meeting participants was restricted to those who attended the

Expert Group meeting in person, both for the discussion and follow-up dialogue.

WHO is committed to ensuring that the highest standards of evidence are used in formulation of

recommendations and has therefore standardised the synthesis process based on the GRADE approach.

The first paper specifically addressing the GRADE approach to diagnostic tests and strategies was published

in 2008 (Schunemann. BMJ 2008; 336:1106-1110) and was made available to the Expert Group in the

background documentation for the meeting.

It was explained that individuals were selected to be members of the Expert Group to carefully represent

and balance important perspectives for the process of formulating recommendations. Therefore the Expert

Group included technical experts, end-users, patient representatives and evidence synthesis

methodologists.

Expert Group members were asked to submit completed Declaration of Interest (DOI) forms. These were reviewed by the WHO legal department prior to the Expert Group meeting. A summary is attached in Annex 2. DOI statements were summarised by the co-chair (WHO-STB) of the Expert Group meeting at the start of the meeting. Selected individuals with intellectual and/or research involvement in the methods were invited as observers to provide technical input and answer technical questions. These individuals did not participate in the GRADE evaluation process and were excluded from the Expert Group discussions when recommendations were developed. They were also not involved in the development of the final Expert Group meeting reports, nor in preparation of the STAG-TB documentation or preparation of the final WHO policy statements.


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3. RESULTS

3.1 Use of IGRAs in diagnosis of active TB

3.1.1 Objectives, reference standards and outcomes

Objective

To assess IGRA test performance in active pulmonary TB suspects and confirmed TB cases in low- and

middle-income settings.

Reference standards

Well-designed diagnostic accuracy studies focus on a representative target population in whom genuine

diagnostic uncertainty exists (i.e. patients in whom clinicians would apply the test in the course of regular

clinical practice). Evidence suggests that diagnostic studies that include only known cases and healthy

controls tend to overestimate test accuracy. Therefore, it was considered that studies simultaneously

evaluating IGRA sensitivity and specificity among active TB suspects represent the highest quality evidence,

while studies evaluating IGRA performance among patients with known active TB (for sensitivity) are of

lesser quality.

Because of the focus on active TB diagnostic accuracy and the high prevalence of LTBI in high TB- burden

settings, IGRA specificity was estimated exclusively among studies enrolling active TB suspects where the

diagnostic workup ultimately showed no evidence of active disease.

Acceptable ‘gold standard’ tests are available to diagnose active TB disease (although these vary according

to local resources). The hierarchy of reference standards (Figure 1.) for active TB was therefore used to

judge the quality of each individual assessment of IGRA diagnostic accuracy. From most to least favourable,

these reference standards included:

1) Culture-confirmation or sputum smear-positivity in high TB incidence settings (defined for this purpose

as ≥50/100,000), where sputum smear microscopy has been shown to have high specificity;

2) Sputum smear-positivity without culture in low or intermediate TB incidence settings (defined for this

purpose as <50/100,000);

3) Clinical diagnosis based on presenting symptoms, radiology and/or response to TB treatment without

microbiological confirmation.

Because the TST remains in widespread use, and because indeterminate IGRA results may affect assay

performance in low-income settings, the following were also evaluated:

1) Observed differences in sensitivity for active TB diagnosis between IGRA and TST;

2) The proportion of IGRA results among patients with active disease which are indeterminate. Primary outcomes

Sensitivity: proportion of individuals with a positive IGRA result among those with culture-positive TB

(indeterminate IGRA results included in the denominator if they occurred in individuals with culture-

positive TB);


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Specificity: proportion of individuals with a negative IGRA result among those ruled out for active TB

disease (indeterminate IGRA results excluded from analysis).

Using the GRADE framework, sensitivity and specificity were interpreted as proxies for patient-important

outcomes: Poor sensitivity would result in false-negative results where TB patients will be missed with

consequences for morbidity, mortality and transmission of tuberculosis. Poor specificity would result in

false-positive results where patients without TB disease will be prescribed unnecessary anti-TB therapy for

six months, with possible consequences including adverse events such as hepatotoxicity and (rarely)

deaths. Secondary outcome

Incremental or added value of IGRAs to determine if these contributed to active TB diagnosis beyond that

established through conventional tests (symptoms, chest radiograph, and sputum smears). Such studies

would be expected to use multivariable analysis to determine the added value of IGRAs.

3.1.2 Search results

The initial search yielded 789 citations. After full-text review of 168 papers, 19 papers were determined to

meet eligibility criteria for IGRA evaluation of active TB in low- and middle-income settings (Annex 2). Three

unpublished reports were also included, for a total of 22 papers. Because some papers included more than

one commercial IGRA, there were 33 unique evaluations (referred to as studies) – 21 of QFT-GIT, and 12 of

T-SPOT – that included a total of 1,815 HIV-uninfected and 1,057 HIV-infected individuals.

3.1.3 Data analysis

Multiple sources of heterogeneity commonly exist when estimates from studies of diagnostic tests are

summarised. Therefore, expected heterogeneity was approached as follows: First, when possible, data

were synthesized separately for each commercial IGRA and by HIV status. The pre-specified sub-groups

minimized heterogeneity related to differences in testing platform (ELISA vs. ELISPOT), antigens used to

elicit IFN-γ release (ESAT-6/CFP-10 vs. ESAT-6/CFP-10/TB 7.7), and test performance related to HIV-

associated host immunosuppression. Second, heterogeneity was visually assessed using forest plots, and

variation in study results attributable to heterogeneity was characterised (I-squared value) and statistically

tested (chi-squared test). Third, pooled estimates were calculated using random effects modelling, which

provides more conservative estimates than fixed effects modelling when heterogeneity is a concern.

For each individual study, all outcomes were assessed where data were available. First, forest plots were

generated to display the individual study estimates and their 95% confidence intervals. Second, bivariate

random effects regression models were used when both sensitivity and specificity could be reported from

the same TB suspect population. Pooling sensitivity and specificity separately can produce biased estimates

of test accuracy; therefore pooled estimates were generated when both sensitivity and specificity were

reported within a study and ranked as higher quality evidence. Third, hierarchical summary receiver

operating characteristic (HSROC) curves were generated to summarize global test performance.

Because of the need to summarize two correlated measures (sensitivity and specificity), and because

substantial inter-study heterogeneity is common, meta-analysis of diagnostic accuracy requires different

and more complex methods than traditional meta-analytic techniques. Graphically illustrating the trade-off

between sensitivity and specificity, HSROC curves differ from traditional Receiver Operating Characteristics

(ROC) in allowing accuracy to vary by each individual study (ie. allowing for random effects, and thus

allowing asymmetry in the plotted curve), and by discouraging extrapolation beyond the available data by

plotting the curve only over the observed range of test characteristics. The HSROC approach is closely


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related to the bivariate random effects regression model. These methods generally produce similar results

and are both recommended by the Cochrane Diagnostic Test Accuracy Working Methods group.

Pooled estimates were calculated when at least four studies were available in any sub-group and

summarized individual study results when fewer than four studies were available. All analyses were

performed using Stata 11 (Stata Corporation, College Station, Texas, USA), including the user-written

“metandi” programme for Stata for bivariate random effects regression and HSROC analyses.

3.1.4 Study characteristics

Of the total studies, 10 (30%) were from low income countries, and 23 (70%) were from middle income

countries. Seventeen studies (52%) included HIV-infected individuals, and 27 (82%) studies involved

ambulatory subjects (i.e. out-patients as well as hospitalized patients). IGRAs were performed in persons

suspected of having active TB in 19 (58%) studies and in persons with known active TB in 14 (42%) studies.

3.1.5 Study quality

The majority of studies satisfied the QUADAS criteria assessed (Table 1), with the exception of patient

spectrum (biased sampling) and blinding. Seventeen (52%) studies did not enrol a representative spectrum

of patients, and nine (27%) studies did not clearly report that assessment of the reference standard was

performed blinded to IGRA results. Industry involvement was unknown in six (18%) studies and

acknowledged in nine (27%) studies, including donation of IGRA kits (6 studies) and work/financial

relationships between authors and IGRA manufacturers (3 studies).

Figure 2. Assessment of study quality using the QUADAS tool

3.1.6 Sensitivity and specificity estimation among TB suspects

A total of 19 studies were identified that simultaneously estimated sensitivity and specificity in TB suspects,

and test accuracy estimates were pooled using bivariate random effects/HSROC methods. Overall, studies

enrolling active TB suspects demonstrated a sensitivity of 83% (95% CI 70-91%) and specificity of 58% (95%

CI 42-73%) for T-SPOT (8 studies), and a sensitivity of 73% (95% CI 61-82%) and specificity of 49% (95% CI

40-58%) for QFT-GIT (11 studies).


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Sensitivity

With the exception of two studies, the sensitivity of IGRAs was assessed based on a positive culture result

(27 studies, 82%) or a positive AFB sputum-smear result in a high TB incidence setting (4 studies, 12%).

Among studies performed in patients with known active TB, 6 (43%) included patients who had been

treated for greater than one week.

HIV-positive: Eleven studies assessed IGRA sensitivity among HIV-positive active TB suspects.

HSROC/bivariate pooled sensitivity estimates were higher for T-SPOT (78%, 95% CI 56-91%, 5 studies) than

for QFT-GIT (62%, 95% CI 41-79%, 6 studies (Figure 3A-3C).

Figure 3A - 3C. Hierarchical summary receiver operating characteristics (HSROC) plot of studies that

reported both sensitivity and specificity in active TB suspects

The summary curves from the HSROC model contain a summary operating point (red square) representing summarised sensitivity

and specificity point estimates for individual study estimates (open circles). The 95% confidence region is delinieated by the area

within the orange dashed line.

Pooled sensitivity estimates did not appreciably change for either T-SPOT (70%, 95% CI 59-82%, 6 studies)

or QFT-GIT (65%, 95% CI 56-73%, 9 studies) when studies evaluating patients with known active TB were

included in the analysis (Figure 4). Pooled sensitivity estimates for both T-SPOT (I-squared 74%, p<0.01) and

QFT-GIT (I-squared 69%, p=0.001) showed significant heterogeneity.


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Figure 4. Sensitivity of QuantiFERON-TB Gold In-Tube and T-SPOT.TB in HIV-positive persons with

confirmed active tuberculosis in low- and middle-income countries

The forest plots display the sensitivity estimates obtained from individual studies and pooled estimates derived from random

effects (DerSimonian-Laird) modelling.

HIV-negative: Eight studies assessed IGRA sensitivity among HIV-negative active TB suspects.

HSROC/bivariate pooled sensitivity estimates for were QFT-GIT were 82%, 95% CI 76-87%, 5 studies; data

were insufficient to report HSROC/bivariate pooled sensitivity estimates for T-SPOT. Pooled sensitivity

estimates were similar for T-SPOT (87%, 95% CI 82-91%, 5 studies) and QFT-GIT (85%, 95% CI 80-90%, 11

studies) when studies evaluating patients with known active TB were included in the analysis (Figure 5).

Pooled sensitivity estimates showed significant heterogeneity for QFT-GIT (I-squared 53%, p=0.02), but not

for T-SPOT (I-squared 6%, p=0.38).


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Figure 5. Sensitivity of QuantiFERON-TB Gold In-Tube and T-SPOT.TB in HIV-negative persons with

confirmed active tuberculosis in low- and middle-income countries

The forest plots display the sensitivity estimates obtained from individual studies and pooled estimates derived from random

effects (DerSimonian-Laird) modelling.

Head-to-head comparisons of QFT and T-SPOT sensitivity: Six studies (four involving HIV-positive subjects

and two involving HIV-negative subjects) reported head-to-head comparisons of T-SPOT and QFT-GIT

sensitivity. Overall, T-SPOT sensitivity was higher but not significantly different from QFT-GIT sensitivity

(sensitivity difference 14%, 95% CI -4% to 33%, p=0.14) (Table 2). Results were similar when restricted to

HIV-positive subjects (sensitivity difference 18%, 95% CI -16% to 51%, p=0.30). Among HIV-negative

subjects, T-SPOT had higher sensitivity (4-20%) in both available studies.


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Table 2. Head-to-head comparison of sensitivity of T-SPOT.TB versus QuantiFERON-TB Gold In-Tube among active TB suspects

Author, Year Country HIV Status Active TB, n (%) Positive T-SPOT

result, n (%)

Positive QFT

result, n (%)

Sensitivity

difference* (%)

Dheda, 2009† South Africa HIV- 15 (31), 15 (29) 14 (93) 11 (73) 20

Ling, 2010† South Africa HIV- 82 (35), 81 (34) 70 (85) 66 (82) 4

Dheda, 2009 South Africa HIV+ 5 (25) 5 (100) 1 (20) 80

Leidl, 2009 Uganda HIV+ 19 (15) 17 (89) 14 (74) 15

Markova, 2009 Bulgaria HIV+ 13 (14) 8 (62) 12 (92) -31

Ling, 2010† South Africa HIV+ 39 (39), 42 (39) 32 (82) 28 (67) 15

* Sensitivity difference (%) is T-SPOT sensitivity (%) minus QFT-GIT sensitivity (%). † Total numbers of active TB suspects evaluated by each IGRA differed within some studies; these are listed in the order T-SPOT, QFT-GIT.


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Head-to-head comparison of TST and IGRA sensitivity: TST sensitivity in the seven studies involving HIV-

negative patients was higher (80%, 95% CI 74-85%) than in the six studies involving HIV-positive patients

(58%, 95% CI 32-84%). Fifteen studies reported head-to-head comparisons of IGRAs (5 T-SPOT and 10 QFT-

GIT) with TST. Overall, IGRA sensitivity was not statistically different than TST sensitivity for either T-SPOT

(sensitivity difference 9%, 95% CI -10% to 28%, p=0.34) or QFT-GIT (sensitivity difference 1%, 95% CI -11%

to 13%, p=0.89) (Figure 6). There was significant heterogeneity for both estimates (I-squared >80%,

p<0.001). Results were unchanged for QFT-GIT when restricted to either HIV-positive or HIV-negative

subjects (data not shown); there were insufficient studies to form HIV-stratified pooled sensitivity

difference estimates for T-SPOT.

Figure 6. Percent sensitivity difference between IGRA and TST results

The forest plots display percent differences (IGRA sensitivity - TST sensitivity) for confirmed active pulmonary TB in individual

studies and pooled estimates derived from random effects (DerSimonian-Laird) modelling.

* Studies of HIV-positive patients.

Specificity

All specificity estimates were determined in TB suspects using HSROC/bivariate techniques. Overall, pooled

specificity was low for both T-SPOT (58%, 95% CI 42-73%, 8 studies) and QFT-GIT (49%, 95% CI 40-58%, 11

studies). When stratified by HIV-status, pooled specificity for QFT-GIT was higher among HIV-positive active

TB suspects (51%, 95% CI 39-64%, 6 studies) than HIV-negative active TB suspects (42%, 95% CI 33-53%, 5

studies). When restricted to HIV-positive active TB suspects, pooled specificity for T-SPOT was 55% (95% CI


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45-64%, 5 studies); an insufficient number of studies were available to estimate pooled specificity for T-

SPOT among HIV-uninfected patients.

3.1.7 Proportion of indeterminate IGRA results

The proportion of indeterminate IGRA results among patients with suspected or confirmed active TB varied

considerably (range 0-26% among studies enrolling 50 or more subjects). The proportion of indeterminate

results was low (3%, 95% CI 1-5%) among HIV-negative patients, regardless of IGRA platform (Figure 7).

However, the proportion of indeterminate results was considerably higher among HIV-positive subjects for

both QFT-GIT (16%, 95% CI 10-21%, 10 studies) and T-SPOT (8%, 95% CI 1-15%, 7 studies)(Figure 8). Results

were similar for HIV-positive subjects when stratified by TB suspects versus known TB cases.

Figure 7. Proportion of indeterminate IGRA results among HIV-negative subjects in low- and middle-

income countries


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Figure 8. Proportion of indeterminate IGRA results among HIV-positive subjects in low- and middle-

income countries

3.1.8 Incremental value of IGRAs for active TB

Two completed but unpublished studies were identified (both from South Africa). These studies used

multivariate methods to estimate the added value of IGRAs beyond conventional tests for active TB. The

first focused on 164 smear-negative TB suspects in South Africa, examining changes in the area under the

receiver operating curve (AUC) resulting from addition of chest radiograph and/or IGRA (QFT-GIT and T-

SPOT) to a baseline clinical prediction model including age, male sex, previous TB, HIV, haemoptysis, weight

loss, and loss of appetite (selected using stepwise regression). When added to the baseline model (AUC

0.75 (0.65-0.85), chest radiograph (AUC 0.80 (0.70-0.89), p=0.12) nor IGRA (T-SPOT, AUC 0.78 (0.68-0.88),

p=0.28; QFT-GIT, AUC 0.78 (0.67-0.88), p=0.30) statistically contributed additional diagnostic information.

Neither QFT-GIT nor T-SPOT had further added value when added to a baseline model including chest

radiograph (Figure 9).


Page | 19

Figure 9. Receiver operating characteristic (ROC) curves for baseline clinical prediction model with and

without addition of IGRA (unpublished) 0.0

00.2

50.5

00.7

51.0

0

Sensitiv

ity

0.00 0.25 0.50 0.75 1.001-Specificity

CXRmodel ROC area: 0.7976 CXR_QFTmodel ROC area: 0.8122

CXR_TSPOTmodel ROC area: 0.8205

Abbreviations: AUC = Area under the receiver operating curve, the probability that a randomly selected case will have a higher test

value than a randomly selected non-case; a perfect test has an area under the curve of 1.0, while a worthless test has an area of

0.5.

The second study examined a cohort in South Africa to report on the added value of QFT-GIT in risk

stratifying 779 individuals (6% active TB prevalence) with HIV-infection prior to initiating isoniazid

preventive therapy. A single positive culture was regarded as definitive evidence of active TB. A baseline

clinical prediction model (AUC 0.72 (0.65-0.79)) including low weight (< 60 kg), prior history of TB, CD4+

count less than 250 cells/mm3, and any single sign or symptom of active TB was selected using p-values

from univariate screening of covariates and stepwise logistic regression. Addition of QFT-GIT to the baseline

model produced no significant increase in AUC (0.74 (0.64-0.82); p=0.41) (Figure 10).


Page | 20

Figure 10. Receiver operating characteristic (ROC) curves for baseline clinical prediction model with and

without addition of QuantiFERON-Gold In-tube and tuberculin skin test (unpublished)

Abbreviations: AUC = Area under the receiver operating curve, the probability that a randomly selected case will have a higher test

value than a randomly selected non-case; a perfect test has an area under the curve of 1.0, while a worthless test has an area of

0.5; TST = tuberculin skin test; QFT-GIT = QuantiFERON-Gold In-tube.

3.1.9 Summary of findings and GRADE evidence profiles

In low- and middle-income countries, the sensitivity of IGRAs in detecting active TB among persons

suspected of having TB ranged from 73-83% and specificity ranged from 49-58%; one in four patients,

on average, with culture-confirmed active TB can therefore be expected to be IGRA-negative in low and

middle income countries, with serious consequences for patients in terms of morbidity and mortality.

There was no evidence that IGRAs have added value beyond conventional microbiological tests

diagnosis of active TB. Among studies that enrolled active TB suspects (i.e. patients with diagnostic

uncertainty), both IGRAs demonstrated suboptimal ‘rule-out’ values for active TB.

Though data were limited, the sensitivity of both IGRAs was lower among HIV-positive patients (around

60-70%), suggesting that nearly one in three HIV-positive patients with active TB will be IGRA-negative.

There was no consistent evidence that either IGRA was more sensitive than the TST for active TB

diagnosis, although comparisons with pooled estimates of TST sensitivity were difficult to interpret due

to substantial heterogeneity.

The few available head-to-head comparisons between QFT-GIT and T-SPOT demonstrated higher

sensitivity for the T-SPOT platform, though this difference did not reach statistical significance.

The specificity of both IGRAs for active TB was low, regardless of HIV status, and suggested that one in

two patients without active TB will be IGRA-positive, with consequences for patients because of

unnecessary therapy for TB and a missed differential diagnosis.

Two unpublished reports reported no incremental or added value of IGRA test results combined with

important baseline patient characteristics (e.g. demographics, symptoms, or chest radiograph findings),


Page | 21

thus not supporting a meaningful contribution of IGRAs for diagnosis of active TB beyond readily

available patient data and conventional tests.

The systematic review focused on the use of IGRAs to diagnose active pulmonary TB, since data

focusing exclusively on extra-pulmonary TB were rare; nevertheless, consensus by the Expert Group

was that recommendations for pulmonary TB could reasonably be extrapolated to extra-pulmonary TB.

3.1.10 Strengths and limitations of the evidence base

Heterogeneity was substantial for the primary outcomes of sensitivity and specificity. Empirical random

effects weighting, excluding studies contributing fewer than 10 eligible individuals and separately

synthesizing data for currently manufactured IGRAs were performed in order to minimize heterogeneity.

No standard criteria exist for defining high TB incidence countries and the World Bank income classification

is an imperfect surrogate for national TB incidence; nevertheless, results were fundamentally unchanged

when restricted to countries with an arbitrarily chosen annual TB incidence of greater than or equal to

50/100,000.

It is likely that ongoing studies were missed despite systematic searching. It is also possible that studies that

found poor IGRA performance were less likely to be published. Given the lack of statistical methods to

account for publication bias in diagnostic meta-analyses, it would be prudent to assume some degree of

overestimation of estimates due to publication bias.

The systematic review focused on test accuracy (i.e. sensitivity and specificity). None of the studies

reviewed provided information on patient-important outcomes, such as showing that IGRAs used in a given

situation resulted in a clinically relevant improvement in patient care and/or outcomes. In addition, no

information was available on the values and preferences of patients.

3.1.11 Final recommendations

The GRADE evidence profiles are provided in Tables 3 and 4. Based on these assessments, the Expert Group

concluded that the quality of evidence for use of IGRAS in diagnosis of active TB was low and

recommended that these tests should not be used as a replacement for conventional microbiological

diagnosis of pulmonary and extra-pulmonary TB in low-and middle-income countries.

The Expert Group also noted that current evidence did not support the use of IGRAs as part of the

diagnostic workup of adults suspected of active TB in low-and middle-income countries, irrespective of HIV

status. This recommendation places a high value on avoiding the consequences of unnecessary treatment

(high false-positives) given the low specificity of IGRAs in these settings.

OVERALL QUALITY OF EVIDENCE LOW

STRENGTH OF RECOMMENDATION STRONG


Page | 22

Table 3. GRADE Evidence Profile:1 Diagnostic accuracy of currently available commercial interferon-gamma release assays (QuantiFERON-TB Gold In-

Tube [QFT-GIT], Cellestis, Australia and T-SPOT.TB [T-SPOT], Oxford Immunotec, United Kingdom) for evaluation of patients with pulmonary TB

in low- and middle-income countries

No of Participants

(studies)

Study

design

Limitations Indirectness Inconsistency Imprecision Publication

Bias

Quality of

evidence (GRADE)

Importance

A. Outcome: Diagnostic accuracy

True Positives

2067 (19) A1

Cross-sectional

No Serious Limitation

A2

No Serious

Indirectness A3

Serious A4

(-1)

Serious A5

(-1) Likely

A6 Low

Critical (7-9)

True Negatives

2067 (19) A1

Cross-sectional


A2

No Serious

Indirectness A3

Serious A4

(-1)

Serious A5

(-1) Likely

A6 Low

Critical (7-9)

False Positives

2067 (19) A1

Cross-sectional


A2

No Serious

Indirectness A3

Serious A4

(-1)

Serious A5

(-1) Likely

A6 Low

Critical (7-9)

False Negatives

2067 (19) A1

Cross-sectional


A2

No Serious

Indirectness A3

Serious A4

(-1)

Serious A5

(-1) Likely

A6 Low

Critical (7-9)

B. Outcome: Proportion indeterminate tests

2872 (33) B1

Cross-sectional

Serious B2

(-1)

No Serious

Indirectness B3

Serious B4

(-1)

No Serious Imprecision

B5 Likely

B6 Low

Critical (7-9)

C. Outcome: Incremental value


Page | 23

943 (2) C1

Cohort Serious C2

(-1)

No Serious

Indirectness C3

No Serious Inconsistency

C4

No Serious Imprecision

C5

Unlikely C6

Low

Critical (7-9)

Footnotes:

1 Quality of evidence was rated as high (no points subtracted), moderate (1 point subtracted), low (2 points subtracted), or very low (>2 points subtracted) based on five criteria: study

limitations, indirectness of evidence, inconsistency in results across studies, imprecision in summary estimates, and likelihood of publication bias. For each outcome, the quality of evidence started at high when there were randomized controlled trials or high quality observational studies (cross-sectional or cohort studies enrolling patients with diagnostic uncertainty) and at moderate when these types of studies were absent. One point was then subtracted when there was a serious issue identified or two points when there was a very serious issue identified in any of the criteria used to judge the quality of evidence. The evidence rankings were considered to be the same for consideration of true positives, false positives, false negatives, and true negatives.

A1 Sensitivity and specificity were determined exclusively among active TB suspects. 19 studies (11 of QFT-GIT and 8 of T-SPOT) were included that assessed the specificity of IGRAs in patients

with suspected active TB.

A2 Study limitations were assessed using the QUADAS tool.

Three (16%) studies did not enrol a representative spectrum of patients. Five (26%) studies did not clearly report that assessment of

the reference standard was performed blinded to IGRA results. A3

Diagnostic accuracy was considered as a surrogate for patient-important outcomes. No studies measured the impact of IGRAs on patient-important outcomes among TB suspects randomized to treatment based on IGRA results; however, the Expert Group members voted not to downgrade for this factor, in part due to the low likelihood of such studies being undertaken. A4

Heterogeneity of studies is visually apparent in the Hierarchical Summary Receiver Operating Characteristics (HSROC) Plots.

A5 Pooled sensitivity derived from the highest quality data (studies enrolling active TB suspects) had relatively wide confidence intervals for T-SPOT.TB (sensitivity 83% (95% CI 70-91%)) and QFT-

GIT (sensitivity 73% (95% CI 61-82%)). Pooled specificity had wide confidence intervals for T-SPOT.TB (specificity 58% (95% CI 42-73%)) and acceptable confidence intervals for QFT-GIT (specificity 49% (95% CI 40-58%)). A6

Data included in the review did not allow for formal assessment of publication bias using methods such as funnel plots or regression tests, and publication bias cannot be ruled out. Although points were not deducted, a degree of publication bias is likely because: 1) literature on IGRAs is expanding rapidly; 2) anecdotal examples of unpublished negative studies on IGRAs exist; and 3) because a sizeable proportion of IGRA studies have some level of industry involvement or support, the risk of unpublished negative studies (or delayed publication of negative studies) is not trivial. B1

33 studies were identified (21 of QFT-GIT and 12 of T-SPOT) from which proportions of indeterminate IGRA results could be derived. B2

Study limitations were assessed using the QUADAS tool. Seventeen (52%) studies did not enrol a representative spectrum of patients.

B3 Please see footnote

A3.

B4 Pooled proportions of indeterminate results showed substantial heterogeneity for HIV-uninfected subjects evaluated with QFT-GIT (range 0-27%, I

2 78%, p<0.001), and HIV-infected subjects

evaluated with both QFT-GIT (range 3-40%, I2 72%, p<0.001) and TSPOT (range 0-25%, I

2 88%, p<0.001).

B5 Precision was acceptable for both IGRAs in both HIV-infected (+/-7%) and HIV-uninfected (+/-3%) subjects.

B6 Please see footnote

A6.

C1

Two completed but unpublished studies were identified (1 QFT-GIT and TSPOT, 1 QFT-GIT) that used multivariate methods to estimate the added value of IGRAs beyond conventional tests for active TB diagnosis. C2

As assessed by QUADAS criteria, one (50%) study did not enrol a representative spectrum of patients. Model specification was undertaken for both studies using traditional parametric statistical methods.


Page | 24

C3 See footnote

A3. In addition, area under the receiver-operating-characteristic curve (AUC) may be a less clinically interpretable measure of risk assessment than risk-reclassification statistics.

C4 Only two studies were available; effect estimates for both studies were in the same direction and consistent.

C5 Imprecision, as evaluated by 95% confidence intervals of the area under the receiver-operating-characteristic curves (AUC), was reasonable for both studies.

C6 Because of the relative novelty of these methods, at this time it is unlikely that studies of IGRA incremental value have been unpublished due to publication bias.


Page | 25

Table 4. GRADE summary of findings – Role of IGRAs for evaluation of patients with pulmonary TB in low- and middle-income countries

Review question: What is the diagnostic accuracy of commercial IGRAs for pulmonary tuberculosis? Patients/population: Adult pulmonary TB suspects and confirmed TB cases in low- and middle-income countries Setting: Outpatients and inpatients Index test: Commercial interferon-gamma release assays (QuantiFERON-TB Gold In-Tube [QFT-GIT], Cellestis, Australia and T-SPOT.TB [T-SPOT], Oxford Immunotec, United Kingdom) Importance: Rapid, accurate, simple test could supplement conventional microbiology and expand testing to peripheral health centers Reference standard: Microbiologic (culture or smear-microscopy) or clinical diagnosis of pulmonary TB Studies: Cross-sectional or cohort

Outcomes: TP, TN, FP, FN Effect % (95% CI)

No. of participants (studies)

What do these results mean given 10% prevalence among suspects being screened for TB?

What do these results mean given 30% prevalence among suspects being screened for TB?

Quality of Evidence

Subgroups

T-SPOT.TB, HIV-infected Sensitivity 78% (56, 91) Specificity 55% (45, 64)

549 (5) With a prevalence of 10%, 100/1000 will have TB. Of these, 78 (TP) will be identified; 22 (FN) will be missed by T-SPOT.TB. Of the 900 patients without TB, 495 (TN) will not be treated; 405 (FP) will be unnecessarily treated.

With a prevalence of 30%, 300/1000 will have TB. Of these, 234 (TP) will be identified; 66 (FN) will be missed by T-SPOT.TB. Of the 700 patients without TB, 385 (TN) will not be treated; 315 (FP) will be unnecessarily treated.

Low

T-SPOT.TB, HIV-uninfected Insufficient data for pooled estimates

364 (3) -- -- --

QuantiFERON-TB Gold In-Tube, HIV-infected

Sensitivity 62% (41,79) Specificity 51% (39, 64)

469 (6) With a prevalence of 10%, 100/1000 will have TB. Of these, 62 (TP) will be identified; 38 (FN) will be missed by QFT-GIT. Of

With a prevalence of 30%, 300/1000 will have TB. Of these, 186 (TP) will be identified; 114 (FN) will be missed by QFT-GIT. Of the

Low


Page | 26

the 900 patients without TB, 459 (TN) will not be treated; 441 (FP) will be unnecessarily treated.

700 patients without TB, 357 (TN) will not be treated; 343 (FP) will be unnecessarily treated.

QuantiFERON-TB Gold In-Tube, HIV-uninfected

Sensitivity 82% (76, 87) Specificity 42% (33, 53)

1304 (5) With a prevalence of 10%, 100/1000 will have TB. Of these, 82 (TP) will be identified; 18 (FN) will be missed by QFT-GIT. Of the 900 patients without TB, 378 (TN) will not be treated; 522 (FP) will be unnecessarily treated.

With a prevalence of 30%, 300/1000 will have TB. Of these, 246 (TP) will be identified; 54 (FN) will be missed by QFT-GIT. Of the 700 patients without TB, 294 (TN) will not be treated; 406 (FP) will be unnecessarily treated.

Low

Outcome Subgroup Effect % (95% CI)

No. of participants (studies)

What do these findings mean? Quality of Evidence

IGRA-TST sensitivity difference*

QuantiFERON-TB Gold In-Tube

1% (-11 to 13%)*

475 (10) This evidence suggests that QFT-GIT is no more sensitive than TST for active TB diagnosis in low- and middle-income countries.

Low

T-SPOT.TB 9% (-10% to 28%)*

206 (5) This evidence suggests that TSPOT is slightly more sensitive than TST for active TB diagnosis in low- and middle-income countries. This evidence should be interpreted with caution given the low number of studies available.

Low

Proportion indeterminate tests

QuantiFERON-TB Gold In-Tube, HIV-uninfected Subjects

4% (1-7%) 1603 (11) This evidence suggests that among HIV-uninfected subjects, the proportion of indeterminate QFT-GIT test results in low- and middle-income countries will be low and similar to high-income countries.

Low

T-SPOT.TB, HIV-uninfected Subjects

3% (1-4%) 494 (5) This evidence suggests that among HIV-uninfected subjects, the

Low


Page | 27

proportion of indeterminate TSPOT test results in low- and middle-income countries will be low and similar to high-income countries.

QuantiFERON-TB Gold In-Tube, HIV-infected Subjects

16% (10-21%) 728 (10) In low- and middle-income countries, the proportion of indeterminate QFT-GIT results among HIV-infected subjects can be expected to be high - in about 16% of the patients tested, clinicians will not be able to use the QFT results for decision making.

Low

T-SPOT.TB, HIV-infected Subjects

8% (1-15%) 666 (7) In low- and middle-income countries, the proportion of indeterminate TSPOT results among HIV-infected subjects can be expected to be high - in about 8% of patients tested, clinicians will not be able to use the TSPOT results for decision making.

Low

Incremental value Neither study demonstrated significant added value over conventional tests for active TB diagnosis, as measured by change in the area under receiver operating curve (AUC).

943 (2) This evidence suggests that after consideration of readily available patient data, neither commercial IGRA can be expected to be useful in diagnosing active pulmonary TB in patients living in low-and middle-income countries.

Low

* Value is IGRA minus TST.


Page | 28

Use of IGRAs in children

Page | 29

3.2 Use of IGRAs in children


Objective 1: Assessment of IGRAs for the diagnosis of LTBI

Reference standards

a. Primary reference standard: Incident active TB disease in groups defined on the basis of results

of IGRA tests and followed in prospective longitudinal studies

b. Secondary reference standard: TB exposure expressed as

Dichotomous exposure (e.g. exposed/unexposed)

Exposure gradient of three or four categories, based on microbiologic indicators (smear

status) of the index case, or proximity to the index case or time of exposure to the index

case.

In these studies, the groups had to be mutually exclusive as described by the study-specific

definition of exposure, but not on other important characteristics nor on the basis of prior

exposure.

Objective 2: Assessment of IGRAs for the diagnosis of active TB disease in children

Reference standards

Reference standards for TB disease:

a. Definite (Confirmed) TB disease

Confirmed bacteriologic disease defined as the presence of at least 1 clinical specimen positive

for M. tuberculosis on culture or AFB smear microscopy positive, or 1 histology sample positive

for necrotising granulomas or nucleic acid amplification test positive for M. tuberculosis, with or

without positive Ziehl-Neelsen stain. (Definition of disease must not include TST or IGRAs)

b. Probable TB Disease

Clinical evidence may include 1) chest radiologic findings consistent with active TB (ideally

confirmed by experienced reviewers), 2) typical symptoms, 3) other radiological evidence of TB,

including extrapulmonary TB (eg. computed brain tomography with classical appearance of TB

meningitis) in conjunction with symptoms 4) exposure to TB, 5) response to appropriate full

anti-TB therapy and 6) must not include TST or IGRA as part of the case definition.

Possible TB was not accepted as a reference standard for active TB.

Reference standards for specificity (‘No TB’ group)

a. TB suspects with symptoms suggestive of active TB, where active TB was excluded;

b. Mixed study groups of children with either suspected active TB or TB contact, where active TB

was excluded by the same investigations that led to the diagnosis of active TB in cases (mainly

clinical and radiological investigations, mycobacterial culture was not necessarily required)

The following were not accepted as non-diseased reference standards:

Healthy children without symptoms or risk factors for TB;

Mixed groups of children with symptoms or TB contact or immigrants without other risk factors,

where it was unclear if active TB was systematically excluded in all;


Page | 30

Objective 3: To review and summarize user-important characteristics of IGRAs, such as impact on

test performance of BCG vaccination status, age, HIV status and TB burden of the setting where

these tests have been used.

Subgroup analysis was performed to assess performance for the diagnosis of active TB across the

following strata of interest:

TST cut-offs at 5, 10, 15 mm;

QFT-Gold versus QFT-Gold IT;

Country where study conducted – dichotomized on the basis of World Bank income index into:

low, lower and upper-middle income, and high income countries;

Country where study conducted – dichotomised on the basis of WHO incidence of smear positive

TB cases (2007), stratified by incidence below or above 25/100,000;

Age of study subjects: stratified analysis using a cut-off of 5 years (mean age, median age if the

mean age was not provided);

BCG status of study subjects: stratified analysis, dichotomised at 50% BCG coverage;

HIV infection dichotomised at 100% HIV-infected in the study population versus < 15% or ‘not

reported’.

Objective 4: To assess operational aspects of IGRAs such as cost, feasibility in children and other

aspects

Outcomes

Data were extracted on the number of positive, negative as well as indeterminate results (if

provided) for each of the reference standards and for each test assessed (IGRAs and TST with

different cut-offs, ie. 5, 10 and 15 mm).

Outcomes were given a hierarchy ranking, depending on their importance for patients receiving the

test. This hierarchy was used in the GRADE framework, when assessing the quality of evidence

provided for each outcome.

For objective 1, the risk of progression to active TB as well as correlation of IGRAs with different

gradients of exposure was ranked as critical. These outcomes, if favorable, will directly have an

impact on the management of child TB contacts and children infected.

For objective 2, sensitivity and specificity of the assays in TB suspects as a surrogate for patient-

important outcomes was rated as critical.

For objective 2, analysis was also completed to assess the impact of indeterminate results on IGRA

test performance. Sensitivity and specificity estimates were calculated with indeterminate results

considered as false negatives. Additional analysis was completed to assess the association between

indeterminate IGRA results and specific factors including age, TB burden of the study setting, HIV co-

infection and BCG vaccination rates in the study population.

Other important outcomes, relevant to all review questions, were the performance of the tests in

high-risk groups such as HIV-infected and young children under five years of age as well as the rate of

indeterminate test results.


Page | 31

3.2.2 Data analysis

Data analysis was performed using SAS version 9.2 (SAS Institute, Inc., Cary, NC) and STATA version

11 (Stata Corporation, College Station, Texas, USA).

Three independent analyses were conducted using three independent types of outcome measures to

assess test performance. As described previously, the three types of outcome measures considered

were incident TB and exposure (Objective 1), and prevalent TB (Objective 2). Since only two

longitudinal studies were identified that estimated incidence of active TB, with very different

methodologies, these studies were simply summarized in descriptive analysis.

Given the small number of pediatric studies available, particularly from LMIC, all analyses were done

for LMIC and HIC combined but also separately for LMIC. GRADE assessment was limited to LMIC

data to ensure consistency with the scope of the Expert Group meeting.

Objective #1 (to evaluate the accuracy and performance of IGRAs for the detection of LTBI) was

addressed using two approaches: studies that measured test performance in children with and

without exposure (i.e. dichotomous exposure) were analyzed collectively whilst studies that

measured test performance in children with varying degrees of exposure (ie. a gradient of exposure)

were analyzed collectively.

For the analysis of dichotomous exposure, the association between test result and TB exposure was

assessed as an odds ratio. Then, results from all studies in this category were pooled together using

both a fixed and a random effects approach.

For the analysis of categorical exposure (more than two categories), the dose-response relationship

was assessed between test result (TST, QFT, or T-SPOT) and TB exposure. For the analyses of

correlation between exposure gradients and prevalence of positive tests, the exposure was

categorized in 3-4 categories, depending on the study. Initially the Spearman correlation between

the categorical test result and the outcome was estimated, followed by a pooled correlation

coefficient for each test with both a fixed and a random effects approach.

In a second approach, the odds ratio was used as the measure of effect to assess performance in

studies that described TB exposure as a gradient. First, the odds ratio was calculated for each level of

exposure relative to the reference group, and then an overall odds ratio was calculated for increasing

exposure category. Both fixed and random effects approaches were used to estimate a pooled

exposure effect across the studies, accounting for the correlation between the category-specific odds

ratios estimated for each study (because they use a common reference category). Inter-study

heterogeneity was also estimated via I-squared statistics.

To address objective #2 (to evaluate the accuracy and performance of IGRAs for the diagnosis of

active TB), studies that measured test performance in children with active disease compared to

children without active disease were analysed collectively. All studies included in this analysis

provided data to estimate test sensitivity (proportion of positive test results among patients with

definite and/or probable TB disease). Indeterminate test results were excluded from the primary

estimate of sensitivity; sensitivity was re-estimated after adding indeterminates as false negative test

results. For studies that included an appropriate group in whom disease was excluded using

methods that met the pre-defined review criteria, the specificity (proportion of negative test results

among patients without TB disease) was calculated. Because many of these studies did not have


Page | 32

non-diseased populations that were judged acceptable, only a portion of studies provided data for

the estimation of test specificity.

A random effects meta-analysis was used to estimate the overall pooled estimates of sensitivity and

specificity and 95% CI. The exact binomial likelihood approach was used, which uses a binomial

distribution to approximate the distribution of the outcome of interest. This approach accounts for

study size, and includes a random effect to account for inter- study heterogeneity. When proportions

are the outcome measure, this approach has been demonstrated to produce less biased estimates of

the pooled effect and the between-study variability. Heterogeneity was assessed of proportions of

subjects with outcomes of interest, within sub-groups defined by covariates of interest, by estimating

the I-squared statistic and associated 95% CIs. To calculate the I-square zero cells were corrected by

0.5.

Significant heterogeneity was expected due to significant variation in study designs and outcome

measures; therefore, when there were sufficient studies, sub-group analyses were performed

stratified by predefined covariates of interest, including World Bank economic status of the study

setting (LMIC versus HIC), TB burden of the study setting, age, BCG vaccination, HIV infection, TST

cut-point, and generation of QFT used. Descriptive statistics were used to examine the relationship

between the frequency of IGRA indeterminate results and co-variates of interest.

Forest plots were generated to display sensitivity and specificity estimates for each study. Data used

to generate forest plots was derived from analysis using all TB disease definitions including definitive

and probable TB. The forest plots display the sensitivity and specificity estimates obtained for each

study and pooled estimates for all studies and for studies stratified by World Bank income category

(HIC vs LMIC). STATA version 11 was used to create the forest plot figures and display SAS generated

data as described above.


240 titles were identified by the electronic database search and from searching reference lists of

selected articles, additional existing databases, review articles and systematic reviews. From these,

68 studies were selected for full text review, of which 36 articles were excluded and 32 articles

included for data analysis (Annex 3).


One of the 32 articles included reported data from two settings and was counted as two separate

studies, i.e. 33 studies.

Five studies were case-control studies and the remaining 28 were cross-sectional studies; 21 studies

were performed in inpatient and/or outpatient settings, 9 studies were household contact studies or

outbreak investigations, and the setting was not clearly defined in 3 studies.

The studies were performed in 18 different countries, of which nine (50%) were high-income (19

studies), four upper-middle (8 studies), two lower-middle (3 studies), and three low-income

countries (3 studies). 42% (14/33) of the studies were performed in LMIC. The incidence of smear

positive TB was <25/100 000 in eight of these countries in 2007, and >25/100 000 in the remaining

ten countries. Studies performed in high-income countries included between 11% and 100%

immigrant children from countries with higher burdens of TB.


Page | 33

A total of 5,922 children were assessed in the 33 studies but results from only 4,505 of these children

were analysed (1,930 children from LMIC), as some sub-groups of children were excluded for not

meeting the criteria of any reference standard. The mean (or median, if mean was not given) age of

children included ranged from 1.9 to 14.6 years with an average of 7.6 years. Overall BCG coverage

ranged between 8-100%, and between 77-100% in LMIC.

Nineteen studies reported on HIV-infection status; of these, only seven studies included any HIV-

infected children (0.5-100%). Two studies, both from LMIC, were performed in HIV-infected children

only.

Eleven studies reported on immune-suppression and of these, two studies from LMIC included

children with immune-suppression (oncology patients, malnourished children), and one study

reported on immune-suppression in HIV-infected children (CD4 count <200) in an upper-middle

income country.

Reference standards

Authors of 21 studies were contacted for clarification of reported data or to request revised data that

met the criteria for the reference standards. Only two studies reported data on incident TB; 18

studies reported data on exposure (10 on dichotomous exposure, 8 on exposure gradients), and 21

studies reported data on prevalent TB. Nine studies met the criteria for assessing specificity of IGRAs

in TB disease as they included a well-defined group in whom TB had been excluded as specified in the

reference standards.

Index tests used

Studies evaluated one or more index tests including T-SPOT (15 studies), QFT-G (10 studies) and QFT-

GIT (21 studies). In three of the QFT-GIT studies, an early version of QFT-GIT kits was used that did

not contain a mitogen-control tube. TST data was provided in 32 studies but only assessed in 30 due

to incorporation bias or interpretation issues in two studies.

3.2.5 Study quality

Thirteen QUADAS quality items for the assessment of quality of diagnostic studies were used and an

additional item on industry involvement added. QUADAS results are shown in Figures 11 and 12.


Page | 34

Figure 11. Methodological quality: Exposure studies

Figure 12: Methodological quality: Studies assessing active TB

Results for relevant QUADAS items show that only 3/21 (14%) of active TB studies and 8/18 (45%) of

exposure studies clearly reported on the sampling methods (consecutive, random or convenient) and

representativeness of their patient spectrum. Blinding of clinicians to IGRA results was reported in

only 6/21 (29%) of studies assessing active TB.

For studies assessing active TB, it remained unclear in 9/21 (43%) whether differential verification

was avoided (whether all children received the reference standard). The execution of the reference

standard (definition of active TB) was described in 17/21 (81%) of studies. However, there was still a

wide variation amongst studies regarding the criteria used for the definition of confirmed or

probable TB, and how detailed these disease categories were described.

Eleven of the 33 studies (33%) were supported by either or both manufacturers of commercial IGRAs,

mainly through donation of test kits.

3.2.6 Test failure and indeterminate results across studies and populations

Test failure of IGRAs was defined as technical errors, failed phlebotomy or an insufficient amount of

peripheral blood mononuclear cells (in the case of T-SPOT) to perform the assay. For TST, failure was


Page | 35

defined as patients not returning for test reading. Failure, especially for TST, was only infrequently

reported. Reported failure rates ranged from 0-7% for QFT-GIT (19 studies), 0% for QFT-G (6 studies),

0-21% for T-SPOT (15 studies) and 0-11% for TST (20 studies).

Average indeterminate results reported across all studies (and including study populations that were

not included in the remaining analysis) were 6.5% for QFT-GIT, 6.4% for QFT-G and 3.5% for T-SPOT

with a wide range among individual studies. In individual studies, high indeterminate rates >10%

were associated with young age (<4 years), co-morbid infections, particularly helminth infection, and

immune-suppression, eg. in cancer patients or HIV-infected children; in some studies no explanation

was found.

3.2.7 Studies assessing incident TB

Only two included studies longitudinally assessed development of TB, both were performed in HIC

and results are therefore not reported here.

3.2.8 Studies assessing exposure

Dichotomous TB exposure

Table 5 describes the characteristics of the ’exposed’ and ’unexposed’ groups in the 10 studies

included (including four studies from LMIC). The definition of the exposure groups varied highly

between studies, either depending on the study setting or the inclusion criteria for each group.

Table 5: Studies with dichotomous expression of exposure included in analysis of test

performance for LTBI, sorted by World Bank income index

Author, year Comparison groups

Description “Exposed” Description “Unexposed”

LM

IC Hansted 2009 HH or school contact No TB contact, no symptoms,

chest radiography normal

Hesseling 2009 Known TB contact No known TB contact

Mandalakas 2008 Known HH contact No known HH contact

Stefan 2010 Known TB contact No known TB contact

HIC

Bianchi 2009 TB contacts, Italian and Immigrant

children Immigrant children without TB

contact

Chun 2008 HH contacts = close contacts Contact outside HH = casual

contacts

Dominguez 2008 Children from contact

investigations

TST + children detected during routine screening (school or

pediatrician)*

Higuchi 2009 Same class as index case

(contact ≥ 90 hours) Same school, different classes as index case (contact < 18 hours)

Lighter 2009 Close contact to TB index case No risk factors for TB exposure

Lucas 2010 Immigrants with HH contact Immigrants without HH contact

* TST was not used for analysis due to incorporation bias

For TST, 10mm was used as the cut-point to define a positive test, except in a few studies which only

reported results of a cut-point of 5mm (2 studies), or 15mm (1 study). One study used a composite

cut off of either 6 or 15 mm depending on risk factors. The overall pooled odds ratio for HIC and

LMIC combined was 1.34 (95% CI: 0.66-2.72), 1.93 (95% CI: 0.98-3.77), and 1.83 (95% CI: 0.67-5.02)

for TST when 5mm, 10mm, or 15 mm was used as the cut-off . For QuantiFERON, the pooled OR was

3.51 (95% CI: 1.85-6.66), and for T-SPOT it was 1.31 (95% CI: 0.76-2.27). All confidence intervals


Page | 36

overlapped, ie. the performance of all assays were similar. was all assays perthere was no statistically

significant difference.

The odds remained positive for a positive QFT (1.30, 95% CI: 0.20-8.32) or T-SPOT (2.24, 95% CI: 0.88-

5.64) result in exposed versus unexposed individuals when analysing data from LMIC separately , but

was less clear for TST with a cut off at 5, 10 or 15 mm (1.04, 95% CI: 0.46-2.36; 0.81, 95% CI 0.38-1.74

and 0.48, respectively). However, the number of studies was small. As for the HIC/LMIC combined

analysis, confidence intervals were overlapping for all three assays, ie. the performance was similar

(Figure 13).

Figure 13. Pooled odds ratios (95% CIs): Concordance of test with dichotomous exposure

In the legend, the number of studies included for each test is indicated in parentheses.

Exposure gradients

Eight studies allowed analysis of the correlation between different grades of exposure (0=least to

3=most exposure) and test results; five of these were performed in LMIC (Table 6). The definitions of

the different grades of exposure varied between these studies, as some studies measured smear

status of an index case, while others measured duration of exposure and proximity to the index case.

The lowest level of exposure was assigned to grade 0 in the dataset, the next level to grade 1 etc. As

a result, even studies using the same measure of exposure, e.g. sputum smear status of the index

cases, did not have the same grades in each level; in some studies contact with index cases with

smear-negative TB was the lowest level of exposure and in other studies the least exposed had

contact with smear-positive TB.


Page | 37

Table 6. Studies with exposure gradients included in analysis of test performance for LTBI, sorted

by World Bank income index

Author, year

Description of assignment to exposure gradients

Grade 0 Grade 1 Grade 2 Grade 3

LM

IC

Adetifa 2010 Different House Different room Same room -

Nakaoka 2006 Community

controls

Exposure to

smear - TB

Exposure to

smear + TB -

Okada 2008 Exposure to

smear - TB

Exposure to

smear + TB

Exposure to

smear ++ TB

Exposure to

smear +++ TB

Petrucci 2008,

Brazil

Exposure to

scanty TB

Exposure to

smear + TB

Exposure to

smear ++ TB

Exposure to

smear +++ TB

Petrucci 2008,

Nepal

Exposure to

scanty TB

Exposure to

smear + TB

Exposure to

smear ++ TB

Exposure to

smear +++ TB

HIC

Bergamini

2009

Exposed to

probable TB

Exposed to

smear -/culture +

TB

Exposed to

smear + TB -

Diel 2008 40-59 hrs

exposure

60 -99 hrs

exposure

100 -199 hrs

exposure

≥ 200 hrs

exposure

Girardi 2007 Low risk, other

students

Intermediate

risk, sharing

some activities

with index case

High risk,

attending

same class

with index

case

-

In LMIC, the pooled correlation coefficient, calculated using a random effects model, was 0.28 (95%

CI: 0.06-0.86, I-squared=0.90) for the association between QuantiFERON result (QFT-G and QFT-GIT

combined) and the gradient of TB exposure. For T-SPOT, the pooled correlation coefficient using a

fixed model (only one study included) was 0.15 (95% CI: 0.02-0.37). For TST, the pooled correlation

coefficient (random effects) was 0.19 (95% CI: 0.02-0.61, I-squared=0.80), 0.22 (95% CI: 0.11-0.39, I-

squared=0.65) when 5 mm and 10 mm were used as the cut-off respectively (no studies used a

15mm cut-off). Confidence intervals overlapped for all three assays, i.e. the performance was similar

(Figure 14). A similar trend was seen if analysis was performed for HIC and LMIC combined (data not

shown).


Page | 38

Figure 14. Pooled estimates: Correlation of tests with exposure gradients

In the legend, the number of studies included for each test is indicated in parentheses.

The slopes of the effect (exposure gradient) were then estimated by regressing the logs of the odds

ratio between each successive higher exposure (Figures 15). With this analytic method, a steeper

slope is associated with a greater change in odds across exposure categories. Hence, the steeper the

slope the better the test is able to distinguish infection across exposure categories. Using either fixed

or random effects models, the slopes estimated for QFT-G and QFT-GIT combined, T-SPOT and TST

employing a 10 mm cut-point were very similar, both in LMIC as well as HIC and LMIC combined.

Estimates were associated with wide and overlapping confidence intervals and as a result no test can

be declared superior.

Figure 15. Regression slopes by exposure gradient

There was no data for TST 15 mm cut-off in LMIC. In the legend, the number of studies included for each test is indicated in

parentheses


Page | 39

3.2.9 Studies assessing active TB

Test performance was assessed in active child TB suspects and cases (sensitivity), and children

categorized as having ‘no TB’ (specificity) according to the predefined reference standards used for

the systematic review. The exact definition for each group of TB suspects/patients varied between

studies and for the ‘no TB’ categories. Because many of these studies did not have non-diseased

populations that were consistent with criteria used in the systematic review, only a portion of studies

provided data for the estimation of test specificity (Table 7).


Page | 40

Table 7. Studies included in analysis of test performance in TB disease, sorted by World Bank

income index

Author, year Active TB: disease categories*

Comparison group: description of “no TB”**

LM

IC

Dogra 2007 Definite/probable TB combined Hospitalized children with clinical suspicion of TB or TB contact, TB

disease was ruled out

Warier 2009 Definite TB, Probable TB Hospitalized children with other

diagnosis, no TB contact

Hansted 2009 Definite TB Reported group not used***

Moyo, unpublished Definite/probable TB combined Children with clinically suspected TB or HH contact, active TB ruled

out

Nicol 2009 Definite/probable TB combined

Children admitted for either clinically suspected TB or TB

contact, active TB ruled out by chest radiography and culture.

Stavri 2009 Definite TB No group reported****

HIC

Bamford 2009 Definite TB, probable TB No group reported

Bergamini 2009 Definite/probable TB combined Reported group not used

Bianchi 2009 Definite/probable TB combined Reported group not used

Chun 2008 Probable TB TB ruled out, other diagnosis

Connell 2006 Definite/probable TB combined Reported group not used

Connell 2008 Probable TB Reported group not used

Detjen 2007 Definite TB Children with other respiratory

illness, low risk for TB

Dominguez 2008 Definite/probable TB combined Reported group not used

Grare 2010 Definite/probable TB combined Reported group not used

Haustein 2009 Definite TB, probable TB Reported group not used

Herrmann 2009 Definite/probable TB combined Children hospitalized for any other

disease, no TB contact

Higuchi 2008 Definite/probable TB combined (detected in school outbreak)

School outbreak investigation, active TB excluded by chest

radiography

Higuchi 2009 Definite/probable TB combined Reported group not used

Kampmann 2009 Definite TB, probable TB Children with risk factors for TB

but disease ruled out, other diagnosis made

Lighter 2009 Definite/probable TB combined Reported group not used

* Definite TB = Culture confirmed disease, Probable TB = Diagnosis made on the basis of symptoms and radiologic findings, no culture result. Definite/probable combined = some cases confirmed but others diagnosed on clinical and radiological criteria only, and results not stratified by method of diagnosis. ** No TB = TB suspects with symptoms suggestive of active TB, or TB contacts where active TB was excluded. *** Reported control group did not meet review criteria for an appropriate control group **** Study assessed active TB group only.

Sensitivity and specificity was calculated for each test. For sensitivity calculations, different disease

categories were considered separately: some studies used an outcome of 1) bacteriologically


Page | 41

confirmed (definite) TB while others used a combined outcome of 2) definite and probable (clinically

and radiologically confirmed) TB combined. These were analyzed separately, and then results from

both types of studies were combined (Table 8 A-C). Analysis counting indeterminate results as

negative was also performed for both IGRAs.

For each category, stratified analysis for test type (TST with different cut-offs and QFT-GIT versus

QFT-G), World Bank income, TB burden based on 2007 WHO TB smear incidence data, BCG

vaccination status, age and HIV infection was performed, excluding indeterminate results.

Confidence intervals for almost all analyses were wide and overlapping, i.e. there were no significant

differences between tests or sub-strata (Table 7). Stratified analysis for LMIC alone provided very

small numbers in the subgroups and did not allow further analysis.

Forest plots for study-specific and pooled estimates of sensitivity and specificity by WB income index

are shown in (Figures 16 - 18). There was a significant amount of heterogeneity among studies;

therefore the results should be interpreted with caution.

Indeterminate results in QFT and T-SPOT lowered the sensitivity of both assays slightly when these

were added to the ‘false-negative’ results, with overlapping confidence intervals (Figure 7). IGRA

indeterminate results were not significantly correlated with any factors including age, HIV status, TB

burden of the setting or BCG vaccination. In addition, there was no difference in the frequency of

IGRA indeterminate results in stratified analysis of these same factors.

Table 8. Diagnostic accuracy of TST, QFT and T-SPOT in active disease in children, including

all acceptable definitions of TB and all countries (HIC and LMIC)

A. TST

ALL TB (definite and probable)

TST*

True positives (sensitivity) False positives (specificity)

N studies N

Pos/Tested

Sensitivity

% (95% CI) N studies

N

Pos/Tested

Specificity %

(95% CI)

Overall 19 386/575 78 (67-89) 7 159/707 84 (66-100)

By TST size

5 mm 13 220/265 91 (84-98) 4 104/217 70 (17-100)

10 mm 16 261/362 81 (71-92) 6 140/621 87 (63-100)

15 mm 11 246/389 67 (50-83) 3 44/131 92 (71-100)

By World Bank category

HIC 14 299/407 81 (73-90) 4 94/217 79 (39-100)

LMIC 5 87/168 65 (31-99) 3 65/490 90 (82-98)

By TB incidence/100,000

<25 13 296/402 83 (73-93) 3 75/131 75 (36-100)

>25 6 90/173 61 (39-84) 4 84/576 88 (71-100)

By BCG vaccination coverage

< 50% 6 57/66 85 (70-100) 1 0/22 100 (85-100)

> 50% 13 329/509 74 (61-88) 6 159/685 78 (57-100)

By age

< 5 yrs 6 90/154 69 (47-92) 4 81/503 90 (74-100)

>5 yrs 13 296/421 81 (69-93) 3 78/204 74 (35-100)


Page | 42

By HIV status**

<15% or

not

reported

18 372/539 79 (69-90) 7 158/707 84 (66-100)

> 100% 1 14/36 39 (0-92) 0 - - * For overall and stratified analysis a TST cut-off of 10mm was preferentially used; for 2 studies TST 5 mm data was used and for 1 study TST 15 mm as this was the only data available.

** Only one study conducted in HIV-infected children.

NR = Not reported

B. QFT-G and QFT-GIT


QFT-G/

QFT-GIT


N studies N

Pos/Tested

Sensitivity


N

Pos/Tested

Specificity

% (95% CI)

Overall 18 335/467 82 (72-91) 7 119/650 90 (78-100)

Overall * 18 335/500 80 (69-91) - - -

By QFT type

QFT-G 6 68/79 94 (86-100) 1 53/82 35 (0-75)

QFT-GIT 13 272/393 77 (65-88) 6 66/568 92 (86-100)


HIC 15 298/394 86 (78-94) 5 65/228 91 (74-100)

LMIC 3 37/73 51 (38-63) 2 54/422 90 (83-95)


<25 14 294/389 86 (78- 93) 4 64/157 82 (59-100)

>25 4 41/78 56 (34- 78) 3 55/493 95 (86-100)

By BCG vaccination coverage

< 50% 6 57/62 93 (85-100) 1 0/21 100 (84-

100)

> 50% 12 278/405 76 (65-86) 6 119/629 86 (72-100)

By age of child

< 5 yrs 5 69/94 86 (71-100) 3 49/419 97 (91-100)

>5 yrs 13 266/373 81 (69-92) 4 70/231 79 (66-100)

By HIV status

< 15% or

NR 17 318/440 83 (74-92) 7 119/650 90 (79-100)

> 100% 1 17/27 63 (16-100) 0 0 - *Indeterminate results included as false-negative.

NR = Not reported


Page | 43

C. T-SPOT


T-SPOT


N studies N

Pos/Tested

Sensitivity


N

Pos/Tested

Specificity %

(95% CI)

Overall 9 194/336 84 (63-100) 4 12/143 94 (87-100)

Overall * 9 194/347 81 (59-100) - - -


HIC 6 126/202 86 (67-100) 2 3/46 95 (84-100)

LMIC 3 68/134 77 (23-100) 2 9/97 93 (83-100)


<25 6 126/202 87 (68-100) 2 3/46 95 (86-100)

>25 3 68/134 73 (29-100) 2 9/97 93 (83-100)

By BCG vaccination coverage**

< 50% 3 42/44 97 (92-100) 1 0/21 100 (84-100)

> 50%** 5 130/239 69 (45-93) 3 11/75 87 (53-100)

By age

< 5 yrs 2 49/86 74 (23-100) 2 8/71 92 (80-100)

>5 yrs 7 145/250 86 (65-100) 2 4/72 95 (88-100)

By HIV status

< 15% or

NR*** 9 194/336 84 (63-100) 4 12/143 94 (87-100)

> 100% 0 0 - 0 0 -

* Indeterminate results included as false-negative.

** BCG vaccination information not provided in one study; study was categorized as >50% BCG vaccinated as national

guidelines recommend neonatal vaccination

NR = Not reported


Page | 44

Figure 16. Forest plots for TST sensitivity and specificity in active TB, separated by World Bank income index

NOTE: Weights are from random effects analysis

.

.

Overall (I-squared = 0.74; 0.6-0.84)

Chun, 2008, Korea

Hansted, 2008, Lithuania

Connell, 2006, Australia

Study

Low Middle Income Countries

Haustein, 2009, UK

Moyo, 2010,South Africa

Stavri, 2009, Romania

Higuchi, 2008, Japan


Kampmann, 2009, UK

High Income Countries

Detjen, 2007, Germany

Subtotal (I-squared = 0.49; 0-0.81)

Dogra, 2006, India

Nicol, 2009, South Africa

Lighter, 2009, US

Bergamini, 2009, Italy

Bamford, 2009, UK

Bianchi, 2009, Italy

Dominguez, 2007, Spain

Herrmann, 2009, France

Grare, 2010, France

Subtotal (I-squared = 0.39; 0-0.68 )

78 (67, 89)

60 (15, 95)

100 (86,100)

Sensitivity

67 (22, 96)

73 (52, 88)

32 (18, 48)

39 (23, 57)

100 (83,100)

88 (47, 100)

73 (60, 83)

100 (88,100)

65 (31, 91)

70 (35, 93)

52 (38, 65)

67 (9, 99)

86 (57, 98)

63 (55, 70)

75 (48, 93)

89 (52, 100)

87 (70, 96)

57 (18, 90)

81 (73, 90)

100

3.5

6.5

Weight

3.7

5.6

5.9

5.7

6.4

4.8

6.2

6.5

28.5

4.4

6.0

3.1

5.4

6.4

5.1

5.0

6.1

3.8

71.5

500 25 50 75 100

TST SENSITIVITY

The measure of sensitivity and specificity is based on TST results using a 10 mm cut-off. Some studies are included that gave only 5 mm or 15 mm results, while one study used a cut-off of either 6 or 15mm according to risk factors.


.

.


Dogra, 2006, India



Subtotal (I-squared = 0.83; 0.69-0.98)

Study


Kampmann, 2009, UK


High Income CountriesChun, 2008, Korea



84 (66, 100)

97 (91, 99)

84 (80, 88)

84 (71, 93)

Specificity

90 (82, 98)

79 (39, 100)

82 (63, 94)

100 (85, 100)

78 (68, 86)

14 (7, 23)

100

14.7

14.7

14.1

Weight

43.4

56.6

13.5

14.4

14.3

14.4

500 25 50 75 100

TST SPECIFICITY


Page | 45

Figure 17. Forest plots for Quantiferon sensitivity and specificity in active TB, separated by World Bank income index


.

.





Chun, 2008, Korea

Stavri, 2009, Romania



Study



Bianchi, 2009, Italy

Grare, 2010, France

Dogra, 2006, India

Bamford, 2009, UK

Kampmann, 2009, UK


Haustein, 2009, UK






Lighter, 2009, US

93 (77, 99)

78 (60, 91)

80 (28, 99)

63 (42, 81)

89 (52, 100)

95 (75, 100)

100 (69, 100)

94 (70, 100)

60 (15, 95)

50 (19, 81)

64 (56, 72)

68 (54, 79)

42 (26, 59)

88 (68, 97)

100 (63, 100)

100 (66, 100)

67 (30, 93)

100 (29, 100)

82 (72, 91)

93 (77, 99)

78 (60, 91)

80 (28, 99)

63 (42, 81)

89 (52, 100)

95 (75, 100)

51 (38, 63)

100 (69, 100)

94 (70, 100)

60 (15, 95)

50 (19, 81)

64 (56, 72)

68 (54, 79)

42 (26, 59)

Sensitivity

88 (68, 97)

100 (63, 100)

100 (66, 100)

67 (30, 93)

86 (78, 94)

100 (29, 100)

100

7.0

6.4

3.4

5.7

5.0

6.8

Weight

15.8

6.3

6.4

3.0

3.9

7.5

6.8

6.1

6.4

5.8

6.1

3.9

84.2

3.4

500 25 50 75 100

QUANTIFERON SENSITIVITY


.

.





Dogra, 2006, India



Chun, 2008, Korea


Low Income Countries

Kampmann, 2009, UK


Study

90 (78, 100)

85 (81, 89)

Specificity

35 (25, 47)

94 (87, 98)

90 (83, 95)

70 (51, 85)

99 (92, 100)

100 (84, 100)

92 (73, 99)

91 (74, 100)

100

15.5

Weight

14.0

15.3

30.8

11.8

15.5

14.7

13.3

69.2

500 25 50 75 100

QUANTIFERON SPECIFICITY


Page | 46

Figure 18. Forest plots for T-SPOT sensitivity and specificity in active TB, separated by World Bank income index


.

.


Warrier, 2009, India




Hansted, 2008, Lithuania



Subtotal (I-squared = 0, 0-0.73)


Bamford, 2009, UK


Study


Kampmann, 2009, UK

84 (63, 100)

42 (28, 56)

100 (59, 100)

86 (67, 100)

Sensitivity

93 (77, 99)

100 (85, 100)

40 (27, 53)

77 (23, 100)

86 (42, 100)

50 (40, 60)

100 (66, 100)

54 (41, 68)

100.00

11.32

10.54

65.45

Weight

11.56

11.84

11.39

34.55

9.38

11.63

10.99

11.35

500 25 50 75 100

TSPOT SENSITIVITY


.

.

Overall (I-squared = 0; 0-0.62 )

Warrier, 2009, India






Kampmann, 2009, UK

Subtotal (I-squared = 0; 0-0.70)

Study

94 (87, 100)

98 (89, 100)

93 (83,100)

84 (71, 93)

100 (84, 100)

88 (69, 97)

95 (84, 100)

Specificity

100

34.9

56.2

21.4

28.2

15.6

43.8

Weight

500 25 50 75 100

TSPOT SPECIFICITY


Page | 47


The majority of IGRA studies in children have been performed in high-income countries and

extrapolation to low- and middle-income settings with high background TB infection rates is not

appropriate. However, based on available data, IGRAs and the TST have very similar accuracy for

diagnosis of LTBI and active TB in children in LMIC settings;

Major methodological inconsistencies between studies had a negative effect on the comparability of

studies and results. A key constraint is the lack of appropriate reference standards for diagnosis of

paediatric TB, limiting the interpretation of estimates of test accuracy in children other than those with

definite TB;

A clear advantage of IGRAs over TST in detecting LTBI in exposed or unexposed individuals or in a

gradient of exposure was not detected;

Lower sensitivity of both IGRAs and TST was found in study populations with >50% BCG coverage. The

reasons are not clear; however, BCG coverage may capture populations from settings with higher

burden of TB, hence with different backgrounds and underlying conditions that may impair test

accuracy, such as co-infections with helminths and malnutrition;

Both IGRAs and TST showed lower sensitivity in HIV-infected children in one study assessed.

Overall, the ability of TST and IGRAs were suboptimal to ‘rule out’ active TB. The main limitation for

assessment of the specificity of the diagnostic assays among ‘no-TB’ groups was the small number of

studies that described adequate methodology to exclude and diagnose active TB;

Indeterminate IGRA results varied across all studies, but higher rates were associated with young age,

immune-suppression or helminth co-infection in individual studies on TB exposure;

In studies on active TB no correlation was found between indeterminate results and age, HIV status, TB

burden or BCG vaccination status;

Studies rarely addressed the operational aspects and implementation feasibility of IGRAs. Cost was

noted as an important and limiting factor. Aspects inherent to the use of IGRAs in children, such as the

difficulty of phlebotomy and the amount of blood needed in young children, are relevant

implementation considerations.


Studies included assessed very different populations in diverse settings, with the biggest challenge and

limitation related to major differences in methodological approaches across studies and non-standardised

definitions of reference standards, TB exposure and TB disease.

Sample sizes in the different studies varied greatly and were less than ten in some of the subgroups

analysed, which adversely impact on generalisability of the findings.

Empirical random effects weighting and separately synthesizing data for currently manufactured IGRAs

were performed in order to minimize heterogeneity; however, heterogeneity remained substantial for the

primary outcomes of sensitivity and specificity.


Page | 48

No standard criteria exist for defining high TB-incidence countries and the World Bank income classification

is an imperfect surrogate for national TB incidence; nevertheless, results were fundamentally unchanged

when restricted to countries with an arbitrarily chosen annual TB incidence of greater than or equal to

25/100,000.

It is likely that ongoing studies were missed despite systematic searching. It is also possible that studies that

found poor IGRA performance were less likely to be published. Given the lack of statistical methods to

account for publication bias in diagnostic meta-analyses, it would be prudent to assume some degree of

overestimation of estimates due to publication bias.

The systematic review focused on test accuracy (ie. sensitivity and specificity) for the diagnosis of active TB

and TB exposure as surrogate for LBTI. None of the studies reviewed provided information on patient-

important outcomes, ie. showing that IGRAs used in a given situation resulted in a clinically relevant

improvement in patient care and/or outcomes. In addition, no information was available on the values and

preferences of patients.

3.2.12 Final recommendations

The GRADE evidence profiles are provided in Tables 9 to 12. Based on these assessments, the Expert Group

concluded that the quality of evidence for use of IGRAS in children was very low and recommended that

these tests should not be used as an alternative to TST in paediatric TB in low and middle-income countries

for the diagnosis of latent TB infection, or as an alternative to TST in the workup of a diagnosis of active TB

disease in children, irrespective of HIV status (strong recommendation).

The Expert Group also notes that there may be additional harms associated with blood collection in

children and that issues such as acceptability and cost have not been adequately addressed in any studies.

OVERALL QUALITY OF EVIDENCE VERY LOW



Page | 49

Page | 50

Table 9. GRADE evidence profile: The performance of IGRAs for the diagnosis of latent tuberculosis infection in children in LMIC

No of participants (studies)

Study design Limitations Indirectness Inconsistency Imprecision Publication bias Quality of evidence (GRADE)

1

Importance

A. Risk of progression to active TB

No studies in LMIC Critical (7-9)

B. Outcome: Performance of IGRAs in studies using a dichotomous measure of exposure as reference standard for LTBI (exposed/unexposed)

229 (4)B1

Mainly cross-sectional

Not seriousB2

Not seriousB3

SeriousB4

(-1) Very serious

B5

(-2) Likely

2 Very Low

Critical (7-9)

C. Outcome: Performance of IGRAs in studies assessing different gradients of TB exposure as reference standard for LTBI

1057 (5)C1

Cross sectional Not seriousC2

Not seriousC3

SeriousC4

Very seriousC5

Likely2

Very Low

Critical (7-9)

The proportion of indeterminate results as well as the influence of HIV-status and young age on IGRA performance were rated as important outcomes (4-6 points) for patients with suspected LTBI. However, due to the small number of studies no subgroup analysis for these outcomes was performed.

Active TB was used as a surrogate measure for LTBI. Tables 10 and 11 describe the evidence profile and summary of findings for studies assessing IGRAs in active TB suspects.

Footnotes

1 The quality of evidence was rated as high (no points subtracted), moderate (1 point subtracted), low (2 points subtracted), or very low (>2 points subtracted) based on five criteria: study

limitations, indirectness of evidence, inconsistency in results across studies, imprecision in summary estimates, and likelihood of publication bias. For each outcome, the quality of evidence started at high, when there were randomized controlled trials or high quality observational studies (cross-sectional or cohort studies enrolling patients with diagnostic uncertainty) and at moderate, when these types of studies were absent. One point was then subtracted when there was a serious issue identified or two points, when there was a very serious issue identified in any of the criteria used to judge the quality of evidence.

2 Data included did not allow for formal assessment of publication bias using methods such as funnel plots or regression tests. Therefore, publication bias cannot be ruled out. Although no points

were deducted, a degree of publication bias is likely because: 1) literature on IGRAs is rapidly exploding and currently unpublished studies may come out in future; 2) there are anecdotal

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examples of unpublished negative studies on IGRAs; and 3) because a sizeable proportion of IGRA studies have some level of industry involvement or support, the risk of unpublished negative studies (or delayed publication of negative studies) is not trivial.

B1 Four studies identified: One evaluated TSPOT, two evaluated T-SPOT and QFT-G, one evaluated T-SPOT and QFT-GIT. In total, QFT-G or QFT-GIT was evaluated in 59 children, T-SPOT in 170

children.

B2 Study limitations were assessed using the QUADAS tool. Tw (50%) studies did not clearly enroll a representative spectrum (patient selection - random, consecutive or convenient - was not

reported). Blinding of laboratory personnel was reported in 3/4 studies. Differential verification and execution of the reference standard were not considered important issues for exposure studies since all children were assessed for exposure.

B3 a) All four studies were performed in upper middle-income countries; the data are not necessarily representative for low-income countries.

b) TB exposure is a surrogate measure for patient important outcomes and does not necessarily classify the target condition (LTBI) correctly. Exposure increases the risk of infection and correctly identified children with infection will highly benefit from preventive chemotherapy. (No points subtracted)

B4 Heterogeneity was assessed by looking at the variation between odds ratios for the different studies. For QFT-G/QFT-GIT the ORs varied between 0.43 and 5, for T-SPOT between 1.5 and 24.

Differences in the definition of exposure groups between the studies may be responsible for the heterogeneity of the results. Two studies were performed in immune-compromised children, one in 100% HIV-infected children, the other in oncology patients. (1 point subtracted)

B5 The 95% CIs for the odds of detecting exposed versus unexposed children were very wide for both QFT-G/QFT-GIT (1.30, 95%-CI 0.2-8.3) and T-SPOT (2.24, 95%-CI 0.88-5.64). The data available

from LMIC was very limited and the sample size for exposure groups 3/4 studies was <50, some subgroups analyzed had a sample size of n=2, which highly increases the risk of imprecision. (2 points subtracted)

C1 Five studies identified: two evaluated QFT-GIT (one without using a mitogen control), one evaluated QFT-G and one evaluated T-SPOT and QFT-GIT. In total, QFT-G or QFT-GIT was evaluated in

773 and T-SPOT in 225 children.

C2 Study limitations were assessed using the QUADAS tool. One study assessed a representative spectrum of children and recruitment was performed in a consecutive manner. Blinding of

laboratory technicians was reported in one study. Like for dichotomous exposure studies, differential verification and execution of the reference standard were not considered important issues for exposure studies since all children were assessed for exposure.

C3 a) Three studies were performed in low-income countries, one in a lower-middle, one in an upper middle income country.

b) TB exposure is a surrogate measure and does not necessarily classify the target condition (LTBI) correctly. Exposure increases the risk of infection and correctly identified children with infection will highly benefit from preventive chemotherapy. (No points subtracted)

C4 Heterogeneity for T-SPOT could not be assessed since there was only one study. Heterogeneity for QFT was assessed using I-squared statistics and considered to be high (90%). Four studies

used microbiological indicators (smear status), one used proximity to the index case as measure of exposure. (1 point subtracted)

C5 The 95% CIs for the pooled random correlation between QFT-studies assessing exposure gradients were wide (QFT-G/QFT-GIT 0.28, 95%CI 0.06-0.86) For T-SPOT, the fixed correlation was 0.15,

95%CI 0.02-0.37. Similar, when calculating regression slopes for exposure gradients, confidence intervals were wide and overlapping for all tests assessed. The data available from LMIC was limited, and the sample sizes assessed small (2 points subtracted)

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Table 10. GRADE summary of findings – IGRAs for LTBI in children Review question: What is the performance of IGRAs for the detection of LTBI in children in LMIC? Patients/population: Children <18 years old in low, lower-middle and upper-middle income countries being screened for LTBI Index test: QuantiFERON-TB Gold [QFT-G], QuantiFERON-TB Gold In-Tube [QFT-GIT], and T-SPOT.TB [T-SPOT]. Importance: Children have a high risk of progression to active TB after infection. Correctly identified children with LTBI benefit from preventive therapy. Reference standards: Incident TB, Exposure (dichotomous and gradient), prevalent TB Studies: Observational studies (cohort, cross-sectional, case-control)

Outcome No. Participants Principal Findings What do these findings mean? Quality of Evidence Importance

Predictive value for active TB

No studies in LMIC

Critical

(7-9)

Performance of IGRAs against dichotomous measure of exposure

QFT-G/QFT-GIT: 59 (3) T-SPOT: 170 (4) TST (10mm): 159 (3)

Pooled Odds ratios

QFT-G/QFT-GIT: OR 1.30 (95% CI 0.20-8.32)

T-SPOT: OR 2.24 (95% CI 0.88-5.64)

TST (10mm): OR 0.81 (95% CI 0.38-1.74)

Children exposed to TB have a higher risk of LTBI, expressed by a higher probability of a positive test for LTBI (QFT, T-SPOT or TST) than in unexposed children. Wide and overlapping confidence intervals indicate similar performance of all three tests.

Very Low

Critical

(7-9)

Performance of IGRAs against exposure gradient

QFT-G/QFT-GIT: 773 (5) T-SPOT: 225 (1) TST (10 mm) 871 (5)

1. Pooled correlation between test and exposure gradient:

QFT-G/QFT-GIT: 0.28 (95%CI 0.06-0.86, I

2 0.90)

T-SPOT (not pooled, 1 study): 0.15 (95% CI 0.02-0.37)

TST (10 mm): 0.22 (95% CI 0.11-0.39, I

2 0.65)

2. Regression slopes

QFT-G/QFT-GIT: 1.84 (95%CI 1.38-2.44, I

2 0.66)

T-SPOT: 1.63 (95%CI 1.12-2.39)

TST (10 mm): 1.73 (95% CI 1.36-2.20, I

2 0.59)

A higher level of exposure to TB indicates a higher risk for LTBI, expressed by a positive correlation between LTBI test and exposure gradients. IGRAs and TST show a similar correlation with exposure gradients (wide and overlapping confidence intervals).

Very Low

Critical

(7-9)

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Table 11. GRADE evidence profile: The diagnostic accuracy of IGRAs for the diagnosis of active tuberculosis in children in LMIC

No of Participants (Studies) Study design Limitations Indirectness Inconsistency Imprecision Publication Bias Quality of Evidence (GRADE)

1 Importance

A: What is the sensitivity of IGRAs in children with active TB?

207 (6)A1

Mainly cross-sectional SeriousA2

(-1) Not serious

A3 Not serious

A4 Very serious

A5

(-2) Likely

2 Very Low

Critical (7-9)

B: What is the specificity of IGRAs in children without TB?

519 (4)B1

Mainly cross-sectional SeriousB2

(-1) Not serious

B3 Serious

B4 Serious

B5

(-1) Likely

2 Very Low

Critical (7-9)

C What is the proportion of indeterminate IGRA results among children assessed for active TB?

656 (5)C1

Mainly cross sectional SeriousC2

(-1) Not serious

C3 Not serious

C4 Serious

C5 Likely

2 Very Low

Important (4-6)

D: What is the diagnostic accuracy of IGRAs in HIV-infected children?

36 (1)D1

Cross-sectional SeriousD2

(1) Not serious

D3 Not applicable

D4 Very serious

D5 Likely

2 Very Low

Important (4-6)

E: What is the diagnostic accuracy of IGRAs in children < 5 years?

471 (2)E1

Cross-sectional SeriousE2

(-1) Serious

E3

Not serious Not applicable

E4 Very serious

E5 Likely

2 Very Low

Important (4-6)

Footnotes

1 The quality of evidence was rated as high (no points subtracted), moderate (1 point subtracted), low (2 points subtracted), or very low (>2 points subtracted) based on five criteria: study

limitations, indirectness of evidence, inconsistency in results across studies, imprecision in summary estimates, and likelihood of publication bias. For each outcome, the quality of evidence started at high, when there were randomized controlled trials or high quality observational studies (cross-sectional or cohort studies enrolling patients with diagnostic uncertainty) and at moderate, when these types of studies were absent. One point was then subtracted when there was a serious issue identified or two points, when there was a very serious issue identified in any of the criteria used to judge the quality of evidence.

2 Data included did not allow for formal assessment of publication bias using methods such as funnel plots or regression tests. Therefore, publication bias cannot be ruled out. Although no

points were deducted a degree of publication bias is likely because: 1) literature on IGRAs is rapidly exploding and currently unpublished studies may come out in future; 2) there are anecdotal examples of unpublished negative studies on IGRAs; and 3) because a sizeable proportion of IGRA studies have some level of industry involvement or support, the risk of unpublished negative studies (or delayed publication of negative studies) is not trivial.

A1 6 studies identified for the assessment of sensitivity (TP and FN) of commercial IGRAs in children with suspected TB or active TB: 3 evaluated T-SPOT, 2 evaluated QFT-GIT, and 1 evaluated

QFT-G. In total, 73 children were evaluated with QFT-G or QFT-GIT and 134 with T-SPOT.

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A2 Study limitations were assessed using QUADAS. One study described a representative spectrum with consecutive patient selection. In 2 studies it remained unclear whether differential

verification was avoided. The execution of the reference standard (definition of active TB) was described in 5/6 studies but definition of the reference standard still varied between different studies and was described more clearly in some than others. Blinding of both laboratory technicians and clinicians remained unclear in the majority of studies. (1 point subtracted)

A3 Four studies were performed in upper middle, 2 in lower middle-income countries and none in low income countries. Hence, the findings may not be generalisable to low-income countries.

Diagnostic accuracy of IGRAs is only a surrogate for patient important outcomes. False negative tests result in children not being diagnosed and started on treatment, which will result in progression of disease, and potentially death. (No points subtracted).

A4 The I

2 statistics showed low to moderate heterogeneity among studies assessing QFT-G/QFT-GIT (32%) with sensitivities ranging from 50 to 63%. Sensitivities for three studies assessing T-

SPOT ranged between 42 and 100%; I-squared was 0%, which may be due to the small number of studies included in the analysis. Indeterminate results, if added to false negative results, lowered the pooled sensitivity for both assays. It can be assumed that the heterogeneity among the studies is caused by factors such as differences in the study populations , number of confirmed versus probable TB cases included in the studies, disease severity, age groups and others.

A5 The 95% confidence interval for pooled sensitivity was wide for both QFT-G/QFT-GIT (51%, 95% CI 38-63%) and T-SPOT (77%, 95% CI 23-100%). The data available from LMIC was very limited

and sample sizes in the individual studies small. (2 points subtracted)

B1 Four studies assessed specificity in children where active TB was excluded: 2 evaluated T-SPOT, and 2 QFT-GIT. In total, 422 children were evaluated with QFT-G or QFT-GIT, and 97 children

with T-SPOT.

B2 Study limitations were assessed using QUADAS. One study described recruitment of a representative spectrum of children in a consecutive manner. Differential verification was avoided in all

studies, and the execution of the reference standard was described in the majority, even though with differing quality. Blinding of laboratory technicians and clinicians remained unclear in the majority of studies. (1 point subtracted)

B3 None of the studies was performed in low-income countries, two in lower, and two in upper middle-income countries. Diagnostic accuracy of IGRAs is a surrogate for patient-important

outcomes. False positive results can lead to a delay in making a correct diagnosis. IGRAs cannot differentiate between disease and infection and positive results may just reflect underlying TB infection. (No points subtracted)

B4 Specificity for QFT-GIT ranged between 85 and 94%, the I

2 statistics of 71% indicates that there is a considerable amount of heterogeneity and suggests that results should be interpreted with

caution. For T-SPOT, specificity ranged between 84% and 98%, I2 statistics was 0 (again, this is likely due to the small number of studies included in this analysis).

B5 The 95% CI for pooled specificity for QFT-G/QFT-GIT (90%, 95%CI 83-95) and T-SPOT (93%, 95%CI 83-100) were relatively narrow. However, the data available for LMIC was limited and the

sample sizes of included studies small. (1 point subtracted)

C1 5 studies assessed commercial IGRAs in children with suspected TB, active TB or ‘no TB’ and included indeterminate results: indeterminate results for QFT-G or QFT-GIT were reported in 3

studies among 524 children, indeterminate results for T-SPOT were reported in 2 studies among 132 children.

C2 Study limitations were assessed using QUADAS. One study described recruitment of a representative spectrum of children in a consecutive manner. Differential verification was avoided and

the execution of the reference standard (definition of active TB) was described in the majority. Blinding of both laboratory technicians and clinicians remained unclear in the majority of studies. (1 point subtracted)

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C3 Three studies were performed in upper middle, 2 in lower middle-income countries and none in low income countries. Hence, the findings may not be generalisable to low-income countries.

Diagnostic accuracy of IGRAs is only a surrogate for patient important outcomes. False negative or indeterminate tests result in children not being diagnosed and started on treatment, which will result in progression of disease, and potentially death. (No points subtracted)

C4 Heterogeneity was assessed by looking at the range of indeterminate results across studies. The overall proportion of indeterminates was 25% for QFT-G, 4.1 for QFT-GIT studies (range 0-5%

in individual studies) and 6.8% for T-SPOT (range 0-8% in individual studies). The QFT-G study showing 25% indeterminates was performed in 100% HIV-infected children with active TB and classifies a high-risk patient group that should be assessed separately for indeterminate results. (No points subtracted)

C5 The number of studies from LMI assessing indeterminate results was limited and the sample size of study populations used for this analysis was small, accounting for serious imprecision. (1

point subtracted)

D1 One study assessed QuantiFERON-TB Gold in 36 HIV-infected children with active TB in Romania (an upper middle-income country.

D2 Study limitations were assessed using QUADAS. The spectrum of patients included in the study was not representative, patient selection was unclear. It also remained unclear whether

laboratory technicians and clinicians were blinded. (1 point subtracted)

D3 The study was performed among HIV-infected children with a diagnosis of TB in Romania, an upper middle-income country. The results may not be generalisable to low-income countries.

Sensitivity of IGRAs is only a surrogate for patient-important outcomes. False negative results, particularly in HIV-infected children, may results in under-diagnosis of disease and, possibly in death. If indeterminate results were added to false negative results the sensitivity was lowered from 63% (indeterminates excluded) to 47% (95%CI 0-100). (No points subtracted)

D4 Only one study – inconsistency therefore cannot be assessed.

D5 The 95% CI for sensitivity of QFT-G in 36 HIV-infected children was very wide (63%, 95%CI 16-100). (2 points subtracted)

E1 In 2 studies evaluating IGRAs for the diagnosis of active TB the mean or median age of children was below five years. One evaluated T-SPOT, and one QFT-GIT. QFT-GIT was assessed in 363

children (36 with active TB, 327 in ‘no TB’ group) and T-SPOT in 108 children (58 with active TB and 50 in ‘no TB’ group).

E2 Study limitations were assessed using QUADAS. The spectrum and patient selection as well as blinding of laboratory technicians was unclear in both studies. Also, studies for this stratum were

selected according to mean or median age since only few studies reported data stratified to age groups. (1 point subtracted)

E3 Both studies were performed in upper middle-income countries, none in lower middle or low-income countries. Hence, the data may not be generalizable to low-income countries. Test

accuracy is only a surrogate for patient-important outcomes. Children under 5 have the highest risk of severe disease and false negative results can result in fatal outcomes. At the same time, false positive results can result in misdiagnosis and prolong the time to correct diagnosis. (No points subtracted)

E4 Heterogeneity could not be assessed since each test was only assessed in one study.

E5 The confidence intervals for sensitivity and specificity of QFT-GIT were small, but wide for T-SPOT. The data from LMIC to address this objective was extremely limited. (2 points subtracted).

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Table 12. GRADE Summary of Findings – IGRAs for the diagnosis of active TB in children

Review question: What is the diagnostic accuracy of IGRAs for the diagnosis of active TB in children in LMIC? Patients/population: TB suspects or active TB patients and control group with ‘no TB’ in low and middle income countries Setting: Mainly mixed, in- and outpatients Index test: QuantiFERON-TB Gold [QFT-G], QuantiFERON-TB Gold In-Tube [QFT-GIT], and T-SPOT.TB [T-SPOT]. Importance: Diagnosis of childhood TB is often a composite of risk factors, clinical signs and symptoms and radiological imaging, since culture confirmation proves difficult. Highly sensitive assays would support a diagnosis of active TB. Reference standard: Culture confirmed TB and probable TB versus ‘no TB’ Studies: Cross-sectional or case-control studies

Outcome Index test

No. of Participants

(Studies)

Effect % (95% CI)

Main findings

What do these results mean given a 10% prevalence among suspects being screened

for TB?

What do these results mean given a 30% prevalence among

suspects being screened for TB?

Quality of Evidence

What is the diagnostic accuracy of IGRAs for active TB?

T-SPOT Sensitivity 143 (3) Specificity 97(2)

Pooled sensitivity 77% (23-100)

Not considerably lower if indeterminate results counted as false negative 76% (18-100)

Pooled specificity 93% (83-100)

Lower in population with >50% BCG coverage 85% (15-100)

With a prevalence of 10%, 100/1000 children will have TB. Of these, 77 will be correctly identified with T-SPOT, 23 will be missed. Of 900 children without TB, 837 will not be treated, 63 will be unnecessarily treated.

With a prevalence of 30%, 300/1000 will have TB. 231 will be correctly identified with T-SPOT, 69 will be missed. Of 700 children without TB, 651 will not be treated, 49 will be unnecessarily treated.

Very Low

QFT-G/ QFT-GIT

Sensitivity 84 (3) Specificity 422 (2)

Pooled sensitivity QFT-G, 1 study: 65% (47-82) QFT-GIT, 2 studies: 36% (29-44) Combined: 51% (38-63)

Pooled sensitivity including indeterminates for QFT-G and QFT-GIT 36% (23-49)

Pooled specificity

With a prevalence of 10%, 100/1000 will have TB. Of these, 65 will be correctly identified by QFT-G, 35 will be missed. 36 will be identified by QFT-GIT, 64 will be missed. Indeterminate results lead to slightly more missed cases. Of 900 children without TB, 90 children will be unnecessarily treated based on QFT-GIT results.

With a prevalence of 30%, 300/1000 will have TB. Of these, 195 will be correctly identified with QFT-G, 105 will be missed. 108 will be identified by QFT-GIT, 192 will be missed. Of 700 children without TB, 70 will be unnecessarily treated based on QFT-GIT results.

Very Low

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QFT-GIT 90% (83-95)

TST Sensitivity 168 (5) Specificity 490 (3)

Pooled sensitivity 65% (31-99) Pooled specificity 90% (82-98)

IGRAs do not perform significantly different from TST

What is the proportion of indeterminate IGRAs among children assessed for active TB?

T-SPOT 132 (2)

Indeterminates/total number of tests 9/132 = 6.82 % Range of % indeterminates across studies 0-8%

What do these results mean? On average, indeterminate IGRA results are below 10% but can be high in certain populations, such as in one study performed in 100% HIV-infected children with active TB, showing 25% indeterminates.

Very Low

QFT-G/ QFT-GIT

QFT-G 36 (1) QFT-GIT 488 (2)

Indeterminates/total number of tests QFT-G: 9/36 = 25% QFT-GIT: 20/488=4.1% (Range of % indeterminates across studies 0-5%)

Page | 58

Performance of IGRAs in HIV-infected children

T-SPOT

No studies

No studies Very Low

QFT-G

Sensitivity

36 (1)

Specificity

No studies

Sensitivity

QFT-G: 63% (16-100)

47% (0-100) if indeterminates counted as FN

Pooled specificity

No studies

With a prevalence of 10%, 100/1000 HIV-infected children will have TB.

Of these, 63 will be correctly identified with QFT-G, 37 will be missed.

With a prevalence of 30%, 300/1000 will have TB.

Of these, 189 will be correctly identified with QFT-G, 111 will be missed.

TST Sensitivity

36 (1)

Specificity

No studies

Sensitivity

39% (0-100)

Specificity

No studies

Sensitivity of TST is lower than of QFT-G, but confidence intervals are wide and overlap.

Performance in children <5yrs

T-SPOT

Sensitivity

134 (3)

Specificity

97 (2)

Pooled sensitivity

77% (23-100)

Pooled specificity

93% (83-100)

With a prevalence of 10%, 100/1000 will have TB. Of these, 77 will be correctly identified by T-SPOT, 23 will be missed. Of 900 children without TB, 837 will not be treated and 63 will be unnecessarily treated.

With a prevalence of 30%, 300/1000 will have TB. Of these, 231 will be correctly identified with T-SPOT, 69 will be missed. Of 700 children with out TB, 651 will not be treated, and 49 will be unnecessarily treated.

Very Low

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QFT-GIT

Sensitivity

36 (1)

Specificity

327 (1)

Pooled sensitivity

35% (30-40)

Pooled specificity

85% (81-89)

With a prevalence of 10%, 100/1000 will have TB. Of these, 35 will be correctly identified by QFT-GIT, 65 will be missed. Of 900 children without TB, 765 will not be treated, 135 will be unnecessarily treated.

With a prevalence of 30%, 300/1000 will have TB. Of these, 105 will be correctly identified by QFT, 195 will be missed. Of 700 children without TB, 595 will not be treated, 105 will be unnecessarily treated.

TST Sensitivity

99 (2)

Specificity

395 (2)

Pooled sensitivity

41% (0-85)

Pooled specificity

83% (81-86)

Sensitivity and specificity of T-SPOT are higher than of QFT-GIT or TST, but the difference is not significant (overlapping confidence intervals)

Use of IGRAs for the diagnosis of LTBI in HIV-infected individuals

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3.3 Use of IGRAs for the diagnosis of LTBI in HIV-infected individuals


Objectives

To assess IGRA test performance in diagnosing LTBI in HIV-infected individuals living in low/middle income countries, with the aim to identify those who would benefit from isoniazid preventive therapy (IPT).

Reference standards and primary outcomes

A major challenge for studies evaluating the performance of IGRAs is the lack of gold standard for LTBI. Consequently, studies were evaluated on three primary outcomes:

Predictive value of IGRAs for development of active TB;

Sensitivity of IGRAs in patients with culture-confirmed active TB (as a surrogate reference standard for TB infection);

Correlation between IGRA and TST results. In addition to the primary outcomes two characteristics that could influence the overall utility of IGRAs were evaluated:

Proportion of indeterminate IGRA results (ie. not interpretable either due to high IFN-γ response in the negative control or low IFN-γ response in the positive control);

Impact of HIV-related immunosuppression (i.e., CD4+ cell count) on test performance (ie. proportion of positive and indeterminate IGRA results, or positive TST results).

Outcome definitions

Incidence of active TB: the number of active TB cases that developed over a specified median duration of

follow-up divided by the number of persons at risk (cumulative incidence), or the number of new active TB

cases divided by the total person-time of follow-up (incidence rate);

Sensitivity: the proportion of individuals with a positive IGRA result among those with culture-positive TB

(including indeterminate IGRA results in the denominator if they occurred in individuals with culture-

positive TB);

Concordance (ie. agreement): the proportion of individuals for whom IGRA and TST results were both

positive or both negative among all individuals tested. In addition, the proportion of positive and

indeterminate IGRA results was determined in the following CD4+ cell count strata: <200 cells/μl and ≥200

cells/μl. To assess the impact of HIV-related immunosuppression, the difference in the proportion of

positive results and the difference in the proportion of indeterminate results was calculated between the

higher and lower CD4+ cell count strata.


The initial search yielded 791 citations. After full-text review of 129 papers evaluating IGRAs in immunocompromised individuals, 29 were determined to meet eligibility criteria. Because some papers included more than one commercial IGRA, there were 37 unique evaluations (hereafter referred to as


Page | 61

studies) – 19 of QFT-GIT and 18 of T-SPOT – that included a total of 5,736 HIV-infected individuals (Annex 4). TST was concurrently performed in 23 (62%) studies.


Of the 37 included studies, 22 (59%) were conducted in low/middle income countries. Among these 22 studies, there was a high degree of variation in study design and study population. 15 (68%) studies included only ambulatory HIV-positive individuals. IGRAs were performed in persons with or suspected of having active TB in 12 studies, asymptomatic HIV-positive persons being evaluated for LTBI in 6 studies, and both types of individuals in 4 studies. Seven (32%) studies had some industry involvement, including donation of IGRA kits (5 studies) and work/financial relationships between authors and IGRA manufacturers (2 studies).

3.3.4 Study quality

A quality assessment was conducted separately for each of the three primary outcomes.

1. Predictive value of IGRAs was appraised for quality with a modified version of the Newcastle-Ottawa

Scale (NOS) for longitudinal/cohort studies. This tool assesses quality in three domains: selection of

cohorts (representativeness of sample and absence of outcome at baseline), comparability of cohorts

(adjustment for potential confounders), and assessment of outcome (blinding and complete

verification);

2. The sensitivity of IGRAs in culture-confirmed active TB was evaluated using a subset of relevant items

from the QUADAS tool.

3. The agreement between IGRA and TST results was evaluated using a subset of relevant items from the

QUADAS tool.

3.3.5 Risk of progression to active TB

One longitudinal study that evaluated the ability of IGRAs to predict future development of active TB among HIV-infected individuals living in a low/middle income country was identified (Table 13). Given the very limited data, two additional studies that were conducted in high income countries were identified and included in the analysis of risk of progression to active TB. Based on the Newcastle-Ottawa scale, all three studies enrolled a representative sample of patients. However, only one study had an adequate duration of follow-up (≥1 year) and all three studies scored poorly on outcome assessment (ie, did not adequately rule-out active TB at baseline or did not adequately evaluate all participants for active TB during follow-up). In addition, all studies had very few incident cases of active TB.

All three studies reported a higher risk of active TB in individuals with a positive IGRA result than in

individuals with a negative IGRA result. However, in the two studies conducted in high income countries,

the absolute difference in cumulative incidence of active TB was not statistically different between persons

with positive and negative QFT-GIT results (8% vs. 0%, risk difference 8%, 95% CI -0.7% to 17%, median

follow-up 19 months) or TSPOT results (10% vs. 0%, risk difference 10%, 95% CI -3% to +23%, median

follow-up 12 months for positive TSPOT results and 3 months for negative TSPOT results). The only study

from a low/middle income country reported that QFT-GIT results stratified HIV-positive individuals into low

risk (1%) and high risk (12%) groups for development of active TB within 6 months of ART initiation.

However, QFT-GIT results were adjusted for CD4+ T-lymphocyte and interpreted using a non-standard cut-

point of 0.00625 IU/mL.


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Table 13. Risk of active tuberculosis in HIV-infected individuals, stratified by IGRA result

IGRA result Active TB (N) Cumulative incidence (%, 95% CI)

Aichelburg 2009 (Austria)

QFT-GIT positive (N=36) 3 8%, 2-22%

QFT-GIT negative (N=705) 0 0%, 0-0.5%

QFT-GIT indeterminate (N=44) 0 0%, 0-9%

Clark 2009 (UK)

TSPOT positive (N=20) 2 10%, 1-32%

TSPOT negative (N=114) 0 0%, 0-3%

TSPOT indeterminate NR NR

Elliot 2009 (Cambodia)*

QFT-GIT positive NR NR

QFT-GIT negative NR NR

QFT-GIT indeterminate NR NR

* Cumulative incidence could not be calculated as the number of persons with active TB in each IGRA result category was not reported Abbreviations: IGRA - interferon-gamma release assay; CI - confidence interval; TSPOT, T-SPOT.TB, QFT-GIT - QuantiFERON-Gold In-tube; NR -Not reported

3.3.6 Sensitivity in culture-confirmed active TB patients

18 studies evaluating the sensitivity of IGRAs in HIV-infected adults with active TB were identified, of which 16 were conducted in low/middle income countries. Eleven (69%) studies did not enrol a representative spectrum of patients (consecutive, ambulatory HIV-positive patients suspected of having active TB. The majority of studies satisfied the remaining QUADAS criteria assessed. Pooled sensitivity estimates were higher for TSPOT (72%, 95% CI 62-81%, 8 studies) than for QFT-GIT (60%, 95% CI 47-75%, 8 studies) (Figure 19). However, results varied widely across studies, resulting in significant heterogeneity in the pooled estimates for both IGRAs (I-squared >70% and p<0.001).


Page | 63

Figure 19. Sensitivity of IGRAs in HIV-positive individuals with confirmed active TB

The forest plots display the sensitivity estimates obtained from individual studies and pooled estimates derived from random effects modeling. Pooled estimates are shown only for sub-groups in which 4 or more studies were available. Abbreviations: IGRA, interferon-gamma release assay; CI, confidence interval; TSPOT, T-SPOT.TB, QFT-GIT, QuantiFERON-Gold In-tube.

Five studies compared head-to-head the sensitivity of IGRAs and TST for diagnosis of active TB in HIV-infected adults. TSPOT was more sensitive than TST in one study (absolute difference 50%, 95% CI 29-71%), less sensitive than TST in one study (absolute difference 18%, 95% CI 2-34%), and as sensitive as TST in one study (absolute difference -3%, 95% CI -17% to +11%). Similarly, QFT-GIT was more sensitive than TST in one study (absolute difference 41%, 95% CI 22-60%) and less sensitive than TST in another study (absolute difference 33%, 85% CI 16-51%).

3.3.7 Agreement between IGRA and TST results

Data on agreement (concordance) between TST and IGRA results in HIV-positive individuals being evaluated

for LTBI were available for 15 studies, of which five were done in low- or middle-income countries. Three

(60%) studies did not enrol a representative spectrum of patients (consecutive, ambulatory HIV-positive

patients being screened for LTBI). The majority of studies satisfied the remaining QUADAS criteria assessed.

TSPOT

Cattamanchi 2010

Dheda (a) 2009

Jiang 2009

Leidl (a) 2009

Ling (a) 2010

Markova (a) 2009

Oni 2010

Rangaka 2010 Pooled Estimate (I-squared 73%, p<0.001)

QFT-GIT

Aabye 2009

Baba 2008

Dheda (b) 2009

Kabeer 2009

Leidl (b) 2009

Ling (b) 2010

Markova (b) 2009

Veldsman 2009 Pooled Estimate (I-squared 77%, p<0.001)

TSPOT

Clark 2007

QFT-GIT

Sauzullo 2010

Uganda

South Africa

China

Uganda

South Africa

Bulgaria

South Africa

South Africa

Tanzania

South Africa

South Africa

India

Uganda

South Africa

Bulgaria

South Africa

United Kingdom

Italy

54 (45, 64)

100 (48, 100)

66 (47, 81)

89 (67, 99)

82 (66, 92)

62 (32, 86)

68 (57, 78)

63 (53, 72)

65 (52, 76)

58 (28, 85)

20 (1, 72)

66 (50, 80)

68 (49, 91)

67 (50, 80)

92 (64, 100)

30 (15, 49) 61 (47, 75)

94 (73, 100)

67 (47, 83)

16

8

12

12

14

7

15

16

15

10

8

14

12

14

13

13

72 (62, 81) 100

0 20 40 60 80 100

B. High Income Countries

A. Low/Middle Income Countries

100


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Of three studies that reported test agreement using kappa values, two reported poor or moderate agreement (kappa 0.4-0.6) and one reported strong agreement (kappa>0.6). When pooled across studies, TSPOT and TST results were concordant in 77% (95% CI 67-88%) of cases but there was significant heterogeneity among individual studies (I2 63%, p=0.04) (Figure 20). There were insufficient studies to calculate pooled estimates for QFT-GIT.

Figure 20. Percent concordance between IGRA and TST results

3.3.8 Indeterminate IGRA results Data on the proportion of indeterminate IGRA results among HIV-positive individuals being evaluated for LTBI were available for 23 studies, of which nine (39%) were done in low- or middle-income countries. The proportion of indeterminate was ≤5% in 4 of 6 studies evaluating T-SPOT (range 0-10%) and two of three studies evaluating QFT-GIT (range 0-11%). For TSPOT, the pooled proportion of indeterminate results was 2% (95% CI 0-3%) and results were consistent across studies (I2 0%, p=0.42). There were insufficient studies to calculate pooled estimates for QFT-GIT.

TSPOT

Hoffmann (b) 2007

Jiang 2009

Mandalakas 2008

Oni 2010

Pooled Estimate (I-squared 63%, p=0.04)

QFT-GIT

Balcells 2008

TSPOT

Hoffmann (a) 2007

Richeldi (a) 2009

Rivas (a) 2009

Stephan 2008

Talati (a) 2009

Pooled Estimate (I-squared 92%, p<0.001)

QFT-GIT

Jones 2007

Luetkemeyer 2007

Richeldi (b) 2009

Rivas (b) 2009

Talati (b) 2009


sub-Saharan Africa

China

South Africa

South Africa

Chile

Switzerland

Italy

Spain

Germany

USA

USA

USA

Italy

Spain

USA

90 (76, 97)

71 (58, 81)

79 (49, 95)

70 (59, 80)

77 (67, 88)

91 (84, 96)

100 (91, 100)

93 (86, 97)

78 (56, 93)

76 (70, 81)

94 (90, 97)

89 (81, 98)

93 (88, 96)

89 (84, 93)

95 (90, 98)

91 (72, 99)

96 (92, 98)

94 (91, 96)

29

28

14

29

100

22

22

11

22

23

100

23

19

20

3

34

100

0 25 50 75 100




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Figure 21. Proportion of indeterminate IGRA results in HIV-infected persons screened for LTBI

3.3.9 Impact of immunosuppression

In 21 studies, IGRA results were available for at least five HIV-infected adults in each of the following CD4+ cell count strata: <200 and ≥200 cells/μl. Among the seven (33%) studies conducted in low/middle income countries, the proportion of positive IGRA results was higher in persons with CD4+ cell count ≥200 cells/μl than in persons with CD4+ cell count <200 cells/μl in four of five studies evaluating TSPOT and both studies evaluating QFT-GIT. In contrast, the proportion of indeterminate IGRA results was higher in persons with CD4+ cell count <200 cells/μl than in persons with CD4+ cell count ≥200 cells/μl in four of 12 studies evaluating TSPOT and six of nine studies evaluating QFT-GIT. For TSPOT, the pooled proportion of positive test results was significantly lower in individuals with CD4+ cell count <200 cells/μl compared with individuals with CD4+ cell count ≥200 cells/μl (difference -18%, 95% CI -34% to -2%) (Figure 22A). However, the pooled proportion of individuals with indeterminate test results was similar among individuals in the two CD4+ cell count strata (4%, -3% to 10%) (Figure 22B). There were insufficient studies to calculate pooled estimates for QFT-GIT.

TSPOT

Hoffmann (b) 2007 Jiang 2009 Leidl (a) 2009 Mandalakas 2008 Oni 2010 Rangaka 2007 Pooled Estimate (I-squared 0%, p=0.42)

QFT-GIT

Balcells 2008 Garfein 2009 Leidl (b) 2009

TSPOT

Clark 2007 Dheda 2005 Hoffmann (a) 2007 Richeldi (a) 2009 Rivas (a) 2009 Stephan 2008 Talati (a) 2009 Pooled Estimate (I-squared 84%, p<0.001)

QFT-GIT

Aichelburg 2009 Brock 2006 Jones 2007 Luetkemeyer 2007 Richeldi (b) 2009 Rivas (b) 2009 Talati (b) 2009 Pooled Estimate (I-squared 58%, p=0.03)

sub-Saharan Africa China Uganda South Africa South Africa South Africa

Chile Mexico Uganda

United Kingdom United Kingdom Switzerland Italy Spain Germany USA

Austria Denmark USA USA Italy Spain USA

5 (1, 17) 0 (0, 5) 4 (1, 9) 10 (1, 32) 4 (1, 10) 1 (0, 7) 2 (0, 3)

0 (0, 3) 11 (4, 25) 4 (1, 9)

2 (0, 11) 3 (0, 18) 13 (5, 26) 2 (0, 5) 0 (0, 8) 3 (1, 6) 14 (10, 18) 5 (1, 9)

6 (4, 8) 3 (2, 5) 5 (2, 9) 5 (3, 8) 6 (3, 12) 2 (0, 13) 2 (1, 4) 4 (3, 6)

4 42 18 1 13 22 100

14 10 8 18 16 18 16 100

21 21 11 14 7 4 21 100

0 25 50




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Figure 22. Impact of immunosuppression on IGRA results A. Proportion of positive IGRA results

TSPOT

Hoffmann (b) 2007

Jiang 2009

Leidl (a) 2009

Mandalakas 2008

Oni 2010 Pooled Estimate (I-squared 44%, p=0.13)

QFT-GIT

Balcells 2008

Leidl (b) 2009

TST

Jiang 2009

Oni 2010

TSPOT

Clark 2007

Dheda 2005

Hoffmann (a) 2007

Richeldi (a) 2009

Rivas (a) 2009

Stephan 2008 Talati (a) 2009 Pooled Estimate (I-squared 0%, p=0.70)

QFT-GIT

Aichelburg 2009

Brock 2006

Jones 2007

Luetkemeyer 2007

Richeldi (b) 2009

Rivas (b) 2009

Talati (b) 2009

Study

sub-Saharan Africa

China

Uganda

South Africa

South Africa

Chile

Uganda

China

South Africa

United Kingdom

United Kingdom

Switzerland

Italy

Spain

Germany USA

Austria

Denmark

USA

USA

Italy

Spain

USA

Country

-26 (-53, 0)

-27 (-61, 8)

5 (-15, 25)

-18 (-62, 26)

-31 (-53, -9) -18 (-34, -2)

-2 (-20, 17)

-23 (-43, -4)

-35 (-59, -11)

15 (-11, 41)

-18 (-45, 9)

-4 (-34, 26)

0 (-19, 19)

1 (-9, 11)

-11 (-45, 22)

-8 (-21, 5) -3 (-7, 1) -3 (-7, 0)

-4 (-6, -1)

-3 (-7, 1)

-7 (-12, -2)

-9 (-14, -4)

-5 (-12, 3)

-18 (-52, 16)

0 (-3, 4)

-8 (-14, -3)

Difference in

% Positive (95% CI)

21

15

27

11

26 100

51

49

50

50

2

1

3

12

1

7 75 100

25

18

14

15

9

1

19

100

39

35

16

10

100

Weight




TST

Jones 2007

Luetkemeyer 2007

Richeldi 2009

Stephan 2008

Pooled Estimate (I-squared %, p=0.67)

USA

USA

Italy

Germany

-4 (-7, -2)

-6 (-12, -0)

-6 (-15, 2)

-2 (-12, 9)

-7 (-10, -3)

-100 0 60 -20 -60 20 * Difference = (% positive CD4 <200 cells/ul) – (% positive CD4 ≥200 cells/ul)

Figure 8. Impact of CD4+ cell count on the proportion of indeterminate IGRA results in


Page | 67

B. Proportion of indeterminate IGRA results

* Difference = (% positive CD4 <100 cells/ul) – (% positive CD4 >200 cells/ul) Data on the impact of immunosuppression on TST results were available for two studies. One study found that the proportion of positive TST results was 35% (95% CI 11-59%) lower in persons with CD4+ cell count <200cells/μl compared to persons with CD4+ cell count ≥200 cells/μl. Data from the second study trended in the opposite direction: the proportion of positive TST results was 15% (95% CI -11% to +41%) higher in persons with CD4+ cell count <200cells/μl compared to persons with CD4+ cell count ≥200cells/μl.


The major limitation was the lack of an adequate reference standard to evaluate the accuracy of IGRAs for diagnosis of LTBI. The majority of studies were small (< 100 patients in 12 of 22 studies), only five studies performed a head-to-head comparison of IGRA and TST results to a reference standard, and there were insufficient studies to perform meta-analysis in many sub-groups.

TSPOT Hoffmann (b) 2007 Jiang 2009 Leidl (a) 2009 Mandalakas 2008 Oni 2010 Pooled Estimate (I-squared 0%, p=0.75)

QFT-GIT Balcells 2008 Leidl (b) 2009

TSPOT Clark 2007 Dheda 2005 Hoffmann (a) 2007 Richeldi (a) 2009 Rivas (a) 2009 Stephan 2008 Talati (a) 2009 Pooled Estimate (I-squared 8%, p=0.37)

QFT-GIT Aichelburg 2009 Brock 2006 Jones 2007 Luetkemeyer 2007 Richeldi (b) 2009 Rivas (b) 2009 Talati (b) 2009 Pooled Estimate (I-squared 67%, p=0.006)

Study

sub-Saharan Africa China Uganda South Africa South Africa

Chile Uganda

United Kingdom United Kingdom Switzerland Italy Spain Germany USA

Austria Denmark USA USA Italy Spain USA

Country

-6 (-30, 18) 0 (-14, 14) 3 (-5, 12) 14 (15, 43) 8 (-5, 0.22) 4 (-3, 10)

0 (-9, 9) -1 (-8, 6)

-3 (-14, 8) -6 (-22, 11) 4 (-27, 36) -2 (-9, 5) 0 (-20, 20) 2 (-5, 9) 8 (-1, 17) 1 (-3, 5)

16 (9, 22) 6 (-1, 14) 23 (10, 35) 9 (1, 17) 4 (-9, 17) -3 (-23, 17) 4 (0, 9) 9 (3, 15)

Difference in % Indeterminate (95% CI)*

7 20 48 5 21 100

12 6 2 29 4 29 19 100

18 17 11 17 10 6 21 100

Weight

-60 -40 -20 0 20 40 60



* Difference = (% indeterminate CD4 <200 cells/ul) – (% indeterminate CD4 ≥200 cells/ul)


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Given that both TST and IGRAs have suboptimal sensitivity and that discordant results are common, it would be relevant to evaluate outcomes when both tests are used, either simultaneously or sequentially, for diagnosing LTBI in HIV-infected persons.

3.3.11 Research gaps

Important key questions remain unanswered despite the substantial body of literature on IGRAs. HIV-infected individuals with a negative IGRA result may have a low risk of progression to active TB, but this result should be confirmed in larger studies that simultaneously perform TST and include a longer duration of follow-up. IGRAs (particularly TSPOT) may be more sensitive than TST in HIV-infected individuals and less affected by advanced immunosuppression. However, these results were not observed consistently in head-to-head comparisons. Future studies should focus on treatment outcomes in HIV-infected individuals randomized to receive IPT based on IGRA results and evaluate the incidence of TB in HIV-infected individuals with discordant IGRA and TST results.


Although WHO recently endorsed IPT as one of three key public health strategies to reduce the impact of TB on persons living with HIV the optimal test for identifying HIV-infected persons who could benefit from IPT remains an unanswered question;

The majority of persons latently infected with TB, including persons co-infected with HIV, do not develop active TB. The clinical utility of any diagnostic test for LTBI is therefore dependent on its ability to identify which persons are truly at increased risk for progression to active TB and could benefit from IPT;

All three studies of the predictive value of IGRAs in HIV-infected individuals showed that IGRAs have poor positive predictive value but high negative predictive value for active TB. While these results suggest that a negative IGRA result is reassuring (no person with a negative IGRA result developed culture-positive TB), the studies had serious limitations, including small sample sizes with short-duration of follow-up and differential evaluation and/or follow-up of persons with positive and negative IGRA results;

Large prospective cohort studies have established that persons with a positive TST have a 1.4 to 1.7-fold higher rate of active TB within one year compared to persons with a negative TST result. Randomised controlled trials in HIV-infected persons demonstrated that IPT confers a 20-60% reduction in the risk of active TB and that this reduction occurs only in persons with positive TST results;

In spite of limited data on predictive value, it has been suggested that IGRAs may have a role for identifying TB infection in HIV-infected individuals given the known decreased performance of TST in immunosuppressed persons. However, neither IGRA was consistently more sensitive than TST in head-to-head comparisons. Data on the impact of immunosuppression on IGRA validity remains unclear.

3.3.13 Final Recommendations

The GRADE evidence profiles are provided in Tables 14 and 15. Based on these assessments, the Expert

Group concluded that the quality of evidence for use of IGRAS in individuals living with HIV infection was

very low and recommended that these tests should not be used as a replacement for TST for the

assessment of LTBI (strong recommendation).

This recommendation also applies to HIV-positive children based on the generalisation of data from

adults;


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Table 14. GRADE evidence profile: The role of IGRAs in the diagnosis of latent tuberculosis infection in HIV-infected individuals

No of Participants (Studies)


1

Importance

A. Outcome: Predictive value of IGRAs for active TB

1100 (3)B1

LMIC: 306 (1)

Prospective cohort

SeriousB2

(-1)

SeriousB3

(-1)

NoneB4

SeriousB5

(-1)

LikelyB6

Very Low

Critical (7-9)

B. Outcome: Sensitivity for active TB (as a surrogate reference standard for LTBI)

1523 (18)D1

LMIC: 1056 (16)


No serious limitations

D2

SeriousD3

(-1) Very Serious

D4

(-2) Serious

D5

(-1) Likely

D6 Very Low

Important (4-6)

C. Outcome: Concordance with TST

2158 (15)E1

LMIC: 401 (5)

Cross-sectional


E2

Very SeriousE3

(-2) Serious

E4

(-1) None

E5

(-1) Likely

E6 Very Low

Important (4-6)

Footnotes * 1

Quality of evidence was rated as high (no points subtracted), moderate (1 point subtracted), low (2 points subtracted), or very low (>2 points subtracted) based on five criteria: study limitations, indirectness of evidence, inconsistency in results across studies, imprecision in summary estimates, and likelihood of publication bias. For each outcome, the quality of evidence started at high when there were randomized controlled trials or high quality observational studies (cross-sectional or cohort studies enrolling patients with diagnostic uncertainty) and at moderate when these types of studies were absent. One point was subtracted when there was a serious issue identified or two points when there was a very serious issue identified in any of the criteria used to judge the quality of evidence. B1

Three longitudinal studies that evaluated the ability of IGRAs to predict future development of active TB were identified. Two were conducted in high income countries (Austria and UK) and one in a low/middle income country (Cambodia). B2

Based on the Newcastle-Ottawa scale, the study samples were considered to be representative. However, only one study had an adequate duration of follow-up (≥1 year), all three studies scored poorly on outcome assessment did not adequately rule-out active TB at baseline or did not adequately evaluate all participants for active TB during follow-up, and all three studies had very few incident TB cases. B3

Two studies were carried out in high income countries; hence the findings may not be generalizable to low/middle income countries. B4

All three studies found that the risk of active TB was higher in IGRA positive compared to IGRA negative patients; but risk of progression to active TB was low in all groups.

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B5 The number of incident TB cases was small in all studies, leading to wide confidence intervals for risk estimates. In the two studies that reported cumulative incidence of TB, the difference

in cumulative incidence of TB between IGRA positive and IGRA negative persons was not statistically significant. B6

Data included in the review did not allow for formal assessment of publication bias using methods such as funnel plots or regression tests. Therefore, publication bias could not be ruled out. Some degree of publication bias was assumed likely because: 1) literature on IGRAs is rapidly exploding and currently unpublished studies may come out in future (despite an attempt to be comprehensive and include unpublished studies); 2) there are anecdotal examples of unpublished negative studies on IGRAs; and 3) because a sizeable proportion of IGRA studies have some level of industry involvement or support, the risk of unpublished negative studies (or delayed publication of negative studies) is not trivial. However, we did not deduct points for this factor.

D1 18 studies were identified: 9 evaluated TSPOT and 9 evaluated QFT-GIT.

D2 Study limitations were evaluated using the QUADAS tool. 12 (67%) studies did not enroll a representative spectrum of patients (ambulatory HIV-infected patients suspected of having active

TB). The majority of studies satisfied the remaining QUADAS criteria assessed. D3

16 (89%) studies were conducted in low/middle income countries. However, sensitivity for active TB may not reflect performance for LTBI and diagnostic accuracy is only a surrogate for patient-important outcomes. D4

There was significant heterogeneity in sensitivity estimates for both TSPOT (range 54-100%, I2 73%, p<0.002) and QFT-GIT (range 20-92%, I

2 78%, p<0.001) in low/middle income countries.

D5 The 95% confidence interval for pooled sensitivity was wide for both TSPOT (72%, 95% CI 62-81%) and QFT-GIT (61%, 47-75%) in low/middle income countries.

D6 Data included in our review did not allow for formal assessment of publication bias using methods such as funnel plots or regression tests. Therefore, publication bias could not be ruled

out. However, no points were deducted as additional negative studies were unlikely to bias the principal finding (sub-optimal IGRA sensitivity).. E1

15 studies were identified: 9 evaluated TSPOT and 6 evaluated QFT-GIT. E2

Study limitations were evaluated using the QUADAS scale. A majority of studies satisfied all QUADAS criteria assessed. E3

Only 5 of 9 studies for TSPOT and 1 of 6 studies for QFT-GIT were conducted in low/middle income countries. In addition, concordance between IGRAs and TST is a poor surrogate for patient-important outcomes. E4

Among studies conducted in low/middle income countries, there was significant heterogeneity in estimates of percent concordance between IGRA and TST for TSPOT (range 70-90%, I2

63%, p=0.04). There was only 1 study of QFT-GIT (concordance 91%). E5

The 95% confidence interval for pooled concordance was within +/10% in most sub-groups.

E6 Data included in the review did not allow for formal assessment of publication bias using methods such as funnel plots or regression tests. Therefore, publication bias could be ruled out.

Some degree of publication bias was assumed likely because: 1) literature on IGRAs is rapidly exploding and currently unpublished studies may come out in future (despite an attempt to be comprehensive and include unpublished studies); 2) there are anecdotal examples of unpublished negative studies on IGRAs; and 3) because a sizeable proportion of IGRA studies have some level of industry involvement or support, the risk of unpublished negative studies (or delayed publication of negative studies) is not trivial. However, no points were deducted for this factor.

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Table 15. GRADE Summary of Findings – Role of IGRAs for diagnosis of LTBI in HIV infected individuals Review question: What is the role of IGRAs in the diagnosis of latent tuberculosis infection (LTBI) in HIV-infected individuals? Patients/population: HIV-infected active TB suspects or HIV-infected persons being screened for LTBI; all ages, all countries (data specific to low- and middle-income countries presented when available). Setting: Outpatients and inpatients. Index test: QuantiFERON-Gold In-tube [QFT-GIT] and T-SPOT.TB [TSPOT]. Importance: The performance IGRAs in diagnosing LTBI among HIV-infected individuals is uncertain; it is unclear if IGRAs should be used to identify HIV-infected persons with LTBI who could benefit from preventive therapy. Reference standard: See hierarchy of reference standards (Fig 1) Studies: Randomized controlled trials, observational studies (cohort, cross-sectional, case-control)

Outcome N Principal Findings What do these findings mean? Quality of Evidence Importance

Predictive value for active TB

1100 (3 studies)

1) TSPOT: Cumulative incidence of active TB higher in IGRA+ compared to IGRA- individuals, but difference not statistically significant (10% vs. 0%, risk difference 10%, 95% CI -3% to +23%). 2) QGT-GIT: Cumulative incidence of active TB higher in IGRA+ compared to IGRA- individuals, but difference not statistically significant (8% vs. 0%, risk difference 8%, 95% CI -0.7% to 17%).

IGRA+ individuals may have a higher risk of progression to active TB than IGRA- individuals, but the risk of progression is low in both groups.

Very Low

Critical (7-9)

Sensitivity for active TB (a surrogate reference standard for LTBI)

1523 (18 studies)

1) TSPOT: Pooled sensitivity 72% (95% CI 62-81%); TSPOT more sensitive than TST in 1 study, less sensitive in 1 study, and as sensitive in 1 study. 2) QFT-GIT: Pooled sensitivity was 61% (95% CI 47-75%). Compared to TST, QFT-GIT more sensitive in 1 study and less sensitive in 1 study.

In low- and middle-income countries, IGRAs have suboptimal sensitivity for active TB and do not consistently have higher sensitivity than TST.

Very Low

Important (4-6)

Concordance with TST

1822 (14 studies)

1) TSPOT: Pooled concordance 77% (95% CI 67-88%). 2) QFT-GIT: 1 study; concordance 91%.

In low- and middle-income countries, IGRAs have moderate concordance with TST.

Very Low

Important (4-6)

Use of IGRAs for screening of healthcare workers

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3.4 Use of IGRAs for screening of health care workers


Objectives

To assess IGRA test performance in screening HCWs using cross-sectional, longitudinal and serial testing

studies. Secondary objectives were to:

a) determine if IGRAs are better correlated than the TST with occupational exposure to TB in cross sectional

studies;

b) estimate the rates of IGRA conversions and reversions, and assess whether IGRA conversions are more

closely associated with recent occupational exposure than TST conversions;

c) to summarise evidence produced by cost-effectiveness analyses and programmatic studies.

Reference standards

A major challenge for studies evaluating the performance of IGRAs is the lack of gold standard for LTBI.

Consequently, studies were evaluated using prevalence and incidence of LTBI, correlation between IGRA

results and an exposure gradient, agreement with TST results.

Primary outcomes

In cross-sectional studies:

a) Prevalence of positive TST (ie. LTBI prevalence) versus positive IGRA and associated risk factors;

b) Concordance (ie. agreement) between TST and IGRA results and factors associated with concordance

and discordance;

In longitudinal studies:

a) Incidence of TST and IGRA conversions and risk factors for conversions,

b) Incidence of TST and IGRA reversions and risk factors for reversions.


Forty-two cross-sectional, longitudinal and serial testing designs using a commercial IGRA assay: QuantiFERON-TB Gold® or In-Tube version and the T-SPOT.TB, for TB screening in HCWs in any setting were evaluated (Annex 5). Overall, only five (12%) were done in high incidence settings, while 37 (88%) were done in intermediate or low-incidence countries. The following studies were excluded: 1) case reports and case series, 2) studies with 10 or fewer participants; 3) reviews and commentaries; 4) letters that did not report original data; 5) studies evaluating the use of IGRAs for treatment monitoring in HCWs (ie: not for diagnostic purposes); 6) short-term serial testing studies (serial testing within one month) and reproducibility studies (which have been systematically reviewed recently; 7) non-commercial/in-house assays; and 8) IGRA testing in the context of known nosocomial outbreaks or point-source exposure (as it was expected that these studies would report higher rates of conversions and reversions by both tests, and that results may not reflect the typical level of LTBI prevalence or conversions in an occupational environment.


Page | 74


Studies varied greatly in their design, execution and outcomes. No meta-analyses were performed as

methods are not defined for heterogeneous diagnostic studies with no gold standard. IGRA performance

varies across populations, therefore, all results were stratified by TB incidence in the countries where the

studies were done (high vs intermediate & low incidence). High incidence countries were defined as

countries with more than 100 estimated incident TB cases per year/per 100,000 population as reported to

WHO. However, due to the variety of study designs and HCW screening guidelines, even within the strata,

study populations included HCWs with varying risk of TB exposure.

Studies were assessed by set criteria which included study design, participants, country, period of recruitment, proportion BCG vaccinated, IGRA methods, TST methods and outcome data, including: baseline TST and IGRA positivity rates, indeterminate rates, concordance between TST and IGRA (agreement and kappa value), predominant type of discordance and correlations found between risk factors and test results.

3.4.4 Study quality

Because IGRA studies in HCWs do not use the conventional diagnostic study design for sensitivity and specificity estimation, the QUADAS checklist was not used to evaluate quality. Selected study features were chosen as quality indicators. These included study design (cross-sectional vs longitudinal), use of standardised, commercial assays, use of standardised tuberculin material (PPD-S in North America, RT23 in Europe) for TST, proportion of indeterminate results and the duration of follow-up in longitudinal studies.

3.4.5 IGRA vs. TST positivity rates in high-incidence countries

Three cross-sectional studies were examined comparing IGRA and TST performance in HCWs in India, Russia, and Vietnam, although TST was not performed in the Russian study. TST and IGRA positivity rates were high in HCWs, ranging from 40% to 66% (Figure 23). IGRA positivity was slightly lower than TST positivity in the two studies comparing TST and IGRAs; however, the difference in estimated prevalence was significant only in the study from Vietnam. The Vietnam study also reported the lowest rate of BCG vaccination among participants at 37.3%, compared to 71% vaccinated in the India study.


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Figure 23. LTBI and TST prevalence in low- and middle-income settings

3.4.6 IGRA conversion and reversion rates in longitudinal, serial testing

Two serial testing studies were identified. One study conducted repeat testing at 0, 6, 12 months and the other tested at 0 and 18 months. Rates of IGRA conversions from these studies ranged from 11.6 to 21%. One of these studies calculated the TST conversion rate, and found 4% conversion after 18 months. One study found that conversion rates varied for both the TST and the IGRA when different cut-offs were used. Neither study reported data to suggest that IGRA conversions were better associated with TB exposure than TST conversions.

Reversion rates in one study ranged from 27% in the first 6 month period to 40% in the second 6 month

period. A second study reported 18-month IGRA reversion rates around 7% among baseline concordant

positives, but up to 70% among those with discordant baseline results (ie: TST negative/IGRA positive).

Overall, serial testing data from low-incidence countries suggest that IGRA results vary greatly during serial

testing, and that rates of conversions may vary depending on the test used and the cut-off used to define

conversions. When simple negative/positive changes are used as cut-offs, IGRAs had a higher conversion

rate than the TST.

There are no data to show that IGRAs perform better than TST in identifying incidence of new TB infections.

0

10

20

30

40

50

60

70

80

Lien, PlosONE, 2009

(Vietnam, 37.3% BCG)

Ozekinci, JIMR, 2007

(Turkey, 67% BCG)

***TSPOT.TB***

Pai, JAMA, 2005

(India, 71% BCG)

Mirtskhulava, IJTLD, 2008

(Georgia, 77.7% BCG)

perc

en

t p

osit

ive (

%)

†TST positivity was computed using a 10mm TST cut-point

TST

IGRA


Page | 76

3.4.7 Association between occupational risk factors and test results in HCWs

One study showed a stronger association between occupational risk factors and IGRA rather than the TST

although confidence intervals overlapped. In studies done in high-income countries, being of foreign birth

or having lived in a high TB incidence country was correlated with either IGRA or TST positivity.

3.4.8 Cost-effectiveness of IGRAs in HCW screening

Limited data exist on cost-effectiveness of IGRAs when used for HCW screening and all studies have been

conducted in low-incidence settings and none accounted for serial testing of HCWs with IGRAs.


The systematic review used a comprehensive search strategy using multiple sources and databases to retrieve relevant studies, including unpublished studies and conference proceedings. Only two studies in low- or middle-income countries were identified. Serial testing data, evidence on the predictive value of IGRAs in HCWs, as well as reproducibility data are still limited even in low-incidence settings.

3.4.10 Research gaps

Given the repeated nature of routine screening of HCWs (eg. annual testing), there are particular issues which may not be relevant in routine practice or contact investigations but become very important during repeated screening. These issue need to be explored in properly designed prospective studies and include test reproducibility, performance of IGRAs when repeated frequently, interpretation of discordant TST and IGRA results, and the IFN-g thresholds (cut-off values) which most accurately distinguish new TB infection (ie. conversion) from random variation.


Prevalence of LTBI in HCWs depends on the test used and the particular TB incidence setting;

Both the TST and IGRAs appear to be associated with markers of TB exposure, but the magnitude of associations varies; TST performance is associated with BCG vaccination, while IGRA performance seems to be unaffected.

IFN-g responses seem to have natural variation and tend to fluctuate around the cut-off, causing apparent conversions and reversions. The exact cause of the conversions and reversions remains unclear, and might indicate spontaneous clearance of TB infection, or dynamic changes within the spectrum of latent TB infection.

The use of IGRAs for serial testing is complicated by lack of data on optimum cut-offs for serial testing, and unclear interpretation and prognosis of conversions and reversions.

Conversion rates are highest when a simple negative to positive change is used to define a conversion. This is true in both high and low incidence settings and has implications for deciding on criteria (cut-offs) for conversions and reversions.

There are no data to show that IGRAs perform better at identifying incidence of new TB infections among HCWs than the TST, irrespective of HIV status.


Page | 77



Group concluded that the quality of evidence for use of IGRAS for screening in health care workers in low-

and middle-income countries was very low and recommended that these tests should not be used in

health care worker screening programmes.

The Expert Group also noted the lack of WHO policy on using the TST in health care worker screening

programmes.




Page | 78

Table 16. GRADE evidence profile: Interferon-γ release assays for tuberculosis screening of healthcare workers in low and middle income countries

No of participants (studies)


1

Importance

A. Efficacy of preventive therapy based on IGRA test results

No studies Critical (7-9)

B. Predictive value of IGRA for active TB


C. Outcome: Correlation of IGRA results with occupational TB exposure

991 (2)

A1

Cross-

sectional

No serious

limitations A2

No serious

IndirectnessA3

Serious

A4

(-1)

Serious

A5

(-1)

Likely

A6

Low

Critical (7-9)

D. Outcome: Correlation between IGRA conversions and occupational TB exposure

No studies

Critical (7-9)

E. Outcome: Sensitivity for active TB (as a surrogate reference standard for LTBI)

No Studies Important (4-6)

F. Outcome: Concordance between IGRAs and TST (cross-sectional)

1,357 (4)

B1

Cross-sectional


B2

Serious

B3

(-1)

Serious

B4

(-1)

Serious

B5

(-1)

Likely

B6

Very Low

Important

(4-6)


Page | 79

G. Outcome: concordance between IGRA and TST conversions (longitudinal)

216 (1)

C1

Longitudinal

No serious

limitations C2

Serious

C3

(-1)

No serious

inconsistency C4

Very Serious

C5

(-2)

Likely

C6

Very Low

Important (4-6)

Footnotes:

1Quality of evidence was rated as high (no points subtracted), moderate (1 point subtracted), low (2 points subtracted), or very low (>2 points subtracted) based on five criteria: imitations,

indirectness, inconsistency, imprecision, and publication bias. For each outcome, the quality of evidence started at high when there were randomized controlled trials or high quality observational studies (cross-sectional or cohort studies with diagnostic uncertainty and direct comparison of test results with culture) and at moderate when these types of studies were absent. One point was subtracted when there was a serious issue identified or two points when there was a very serious issue identified in any of the criteria used to judge the quality of evidence.

A1 2 studies were identified evaluating an association between test positivity and occupational exposure to TB. These studies compared only QFT and the TST.

A2 Study limitations were assessed using select quality indicators. Studies satisfied majority of selected quality indicators.

A3 Some indirectness in the choice of reference standard was recognised although the studies were not downgraded for indirectness.

A4 Two studies evaluated the association between 5 variables of occupational exposure to TB and test positivity, estimates ranged from OR=1.28-5.09.

A5 Only 50% of estimates of association of test positivity and exposure reached statistical significance, 95% confidence intervals ranged from: 0.68-9.33. With only two studies, imprecision may

be a concern.

A6 Data included in this review did not allow for formal assessment of publication bias using methods such as funnel plots or regression tests. Therefore, publication bias could not be ruled out.

Although no points were deducted, some degree of publication bias was considered likely because: 1) literature on IGRAs is rapidly exploding and currently unpublished studies may come out in future (despite an attempt to be comprehensive and include unpublished studies); 2) there are anecdotal examples of unpublished negative studies on IGRAs; 3) because a sizeable proportion of IGRA studies have some level of industry involvement or support, the risk of unpublished negative studies (or delayed publication of negative studies) is not trivial.

B1 4 cross-sectional studies were identified: 3 evaluated a previous version of the QFT, 1 study evaluated only the TSPOT.TB.

B2 Study limitations were assessed using select quality indicators as the QUADAS scale was not appropriate for concordance studies. Majority of studies satisfied selected quality indicators.

B3 Concordance between IGRAs and the TST is a poor surrogate for patient important outcomes.

B4 Among studies conducted in low- and middle-income countries, there was moderate heterogeneity in estimates of percent agreement between TST and IGRAs (Range: 50-81%).


Page | 80

B5 Due to heterogeneity in effect estimates we could not pool concordance. However, confidence intervals for estimates of concordance for individual studies were wide, and with only 4

studies, imprecision may be a concern

B6 Data included in the review did not allow for formal assessment of publication bias using methods such as funnel plots or regression tests. Therefore, publication bias could not be ruled out.


C1 1 longitudinal study was included which assessed concordance between TST and IGRA conversions, using the QFT test.

C2 Study limitations were assessed using select quality indicators as the QUADAS scale was not appropriate for concordance studies. Both studies satisfied the majority of selected quality

indicators.

C3 This study was conducted in a low middle income country. Concordance between IGRA and the TST conversions is a poor surrogate for patient important outcomes, and may not be an

appropriate reference standard.

C4 This study estimated fair concordance between QFT and TST conversions (96%).

C5 Only 1 study was identified with a small number of participants (n=216).

C6 Data included in this review did not allow for formal assessment of publication bias using methods such as funnel plots or regression tests. Therefore, publication bias could not be ruled out.



Page | 81

Table 17. GRADE summary of findings – IGRAs for tuberculosis screening of healthcare workers in low and middle income countries

Review question: What is the role of IGRAs in the diagnosis of latent tuberculosis infection (LTBI) in health care workers (HCWs)? Study Population: Healthcare workers being screened for LTBI, all ages, from middle and low income countries. Setting: Occupational screening of HCWs for LTBI Index test: QuantiFERON-Gold or Gold In-tube (QFT) and TSPOT.TB Importance: The performance of IGRAs in diagnosing LTBI in HCWs is uncertain, it is unclear if IGRAs should be used in HCWs to identify those who could benefit from preventive therapy. In particular, it is unclear whether IGRA conversions identify those who could benefit from preventive therapy. Reference standard: See hierarchy of reference standards (Figure 1) Studies: Observational studies (longitudinal cohort, cross-sectional, case-control)

Outcome No. Partici-pants

Principal Findings What do these findings mean?

Quality of Evidence

Importance

Efficacy of preventive therapy based on IGRA test results

No Studies in HCWs

Critical (7-9)

Predictive value of IGRA for active TB

No Studies in HCWs

Critical (7-9)

Correlation between IGRA positivity and occupational TB exposure

991 (2 studies)

1) TSPOT.TB: No studies evaluated TSPOT.TB 2) QFT: All 5 comparisons gave positive estimates for the association between test positivity and occupational exposure (OR=1.28-4.15), 3/5 reached statistical significance. 3) TST: All 5 comparisons gave positive effect estimates (OR=1.33-5.09), 2/5 reached statistical significance.

Data were limited on TSPOT.TB and from low and middle income settings. Occupational exposure was associated with positivity for both tests, although this was not always significant. There is no strong evidence that IGRAs are more strongly correlated with occupational TB exposure than TST.

Low

Critical (7-9)


Page | 82

Correlation between IGRA conversions and occupational TB exposure

No Studies in HCWs

Critical (7-9)

Sensitivity for active TB (as a surrogate reference standard for LTBI)

No Studies in HCWs

Important (4-6)

Concordance between TST and IGRAs

1,357 (4 studies)

In low and middle income studies, agreement between IGRA and TST results ranged from 50.2%-81.4%. While IGRA consistently estimated a lower rate, this difference was significant in only 2/4 cases.

Concordance was fair to poor in low and middle income settings. Both tests provide similar estimates of prevalence in low and middle income countries.

Very Low

Important

(4-6)

Concordance between IGRA and TST conversions

216 (1 study)

This study found 96% agreement between test conversions (QFT & TST).

IGRA and TST conversions show moderate concordance. Data are limited in all settings.

Very Low

Important

(4-6)

Use of IGRAs in contact screening and outbreak investigation

Page | 83

3.5 Use of IGRAs in contact screening and outbreak investigations


Objectives The primary objective was to assess the accuracy and performance of IGRAs for the detection of latent TB infection (LTBI) in contacts and outbreak settings in low and middle-income settings. A secondary objective was to evaluate the factors (specifically TB exposure), associated with IGRA positivity in these settings.

Reference standards TB exposure was defined as exposure to an infectious index case. TB exposure as a reference standard may be captured in a variety of ways, either as a dichotomous variable (exposed v. unexposed) or as a gradient (less exposed to more exposed using contact scores, measures of proximity or duration, household membership, sharing of a room or bed, etc.), based on a wide range of potential classifications.

Studies employing exposure gradients were classified broadly into two categories: a) Exposure gradients based on microbiologic characteristics of the index case (eg. smear status, graded as 3+,

2+, and 1+ ) b) Exposure gradients based on proximity/duration with the index case, including:

Close versus casual contact Household member versus not The so-called Senegal/Gambia gradient (same bed, same room, same house) Hours spent with the index case

Studies employing exposure as dichotomous variables were grouped into two categories: a) Smear-positive versus smear-negative index case b) Exposed versus non-exposed Outcomes For studies using a dichotomous measure of exposure, both exposed and unexposed participants must have been represented in the sample population, and the TST and or IGRA tests could not have been used to classify exposure status of participants.

Apart from exposure gradient analysis, concordance between TST and IGRA results among contacts were evaluated, as well as the rates of conversions and reversions among contacts using both tests.


After a full text review of 99 studies, 65 studies conducted in high income countries were excluded, as were 18 studies using pre-commercial and in-house IGRAs. 16 studies (14 original manuscripts and 2 unpublished studies) involving 4,854 study participants were determined to meet the eligibility criteria (Annex 6).


Page | 84

3.5.3 Data analysis

Given the potential heterogeneity across populations and tests, and expected variations in how various studies constructed exposure gradients, a meta-analysis was not considered appropriate. A narrative synthesis was primarily used, involving detailed tables and plots, stratified by type of assay and type of study design (cross-sectional or longitudinal) as well as exposure category (dichotomous or exposure gradient).


75% of studies were carried out in middle-income countries (South Africa, Lithuania, Brazil, Turkey, Taiwan, India, and Nigeria). The remaining studies were done in low-income countries (Cambodia, Gambia, Nepal and Zambia).

Most studies were small and ranged from 39-301 participants, the larger ones having been conducted in India , Gambia, South Africa and Brazil. However, the inclusion of a large unpublished contact study from Zambia doubled the total sample size (2,211 study participants). All studies included BCG vaccinated participants. HIV was frequently not reported, but when it was reported rates were low (0-1.5%) with the exception of the Zambia study which reported HIV infection rates around 38% in the (adult)study population, and one other study which reported a HIV infection rate of 5% (paediatric population).

Only one study did not include household contacts. This study evaluated health care workers exposed to a smear-positive TB case. The remaining 15 studies all included household contacts, while 3 studies also included school or work contacts. Nine (56%) of the included studies examined child contacts exclusively. A further 3 studies included both child and adult contacts while 4 studies include only adult contacts. Depending on the study design, most studies contained only known contacts of active TB cases; however 5 studies did recruit a comparison group with no known TB exposure.

3.5.5 Study quality

Because contact studies do not use conventional diagnostic study design for sensitivity and specificity estimation, the QUADAS checklist was not used to evaluate quality. Selected study features were chosen as quality indicators. These included study design (cross-sectional vs longitudinal), use of standardised, commercial assays, use of standardised tuberculin material for the TST (PPD-S in North America, RT23 in Europe), timing of IGRA blood draw and TST application, proportion of indeterminate results, reporting on inclusion/exclusion criteria, reporting on how participants were sampled, whether personnel performing test were blinded to other test results and duration of follow-up in longitudinal studies. Quality was not assessed for the two unpublished studies as only preliminary reports were available. Among the 16 studies evaluated, 12 were cross-sectional in design. The included studies varied in quality, with several quality indicators frequently not reported. For example, only 3/14 studies reported whether study personnel had been blinded to other test results (or TB exposure) when performing and interpreting test results; 7/14 studies did not report the sequence of testing (eg. TST followed by IGRA); 5/15 studies (33%) reported some kind of industry involvement, most frequently the provision of test kits at no cost (n=4) ), while one study reported one of its authors having been a paid consultant of the manufacturer of the IGRA test kits evaluated (Table 18).

Study comparability: Only 4 studies presented adjusted odds ratios, and adjusted for different factors: All 4

adjusted for age, 3 also adjusted for sex, 2 adjusted for ethnicity as well as age and sex, and one study adjusted


Page | 85

for a number of additional factors. In the remaining studies which did not present adjusted estimates, residual

confounding was a concern.

Ascertainment of test outcome: Two critical issues in performing and interpreting the tests (both IGRAs and

the TST) were identified: Firstly, previous research has suggested a boosting effect on the IGRA if the TST is

performed prior to blood being drawn. Seven studies did not report on the timing or sequence of testing, 6

studies reported that blood was drawn prior to the implementation of the TST (avoiding any chance of a

boosting effect). Only one study reported performing the TST immediately prior to the blood draw and one

study performed blood draw one month after the TST.

Secondly, only 3 studies reported that personnel had been blinded to previous test results during testing.

Ascertainment bias could therefore not be ruled out for the remaining studies.

3.5.6 Agreement between IGRA and TST Results

Data on agreement or concordance between IGRA and the TST were available for all 16 studies. One study included data from two separate countries, Brazil and Nepal. Given inherent difference in the study populations these cohorts were analysed separately and are presented as separate studies. The prevalence of positive tests varied greatly between studies and across assays. Prevalence of positive TST ranged from 22% in a study of children ≤5 years old to 84.6% in a cohort of adult HCWs exposed to a smear-positive TB case. Prevalence of positive QFT tests ranged from 10.3% to 63.2% and TSPOT.TB positivity ranged from 17.8% to 75% (Figure 24).


Page | 86

Figure 24. Studies evaluating concordance between TST and IGRAs

0

10

20

30

40

50

60

70

80

90

100

Nak

aoka

Ade

tifa

(200

7)

Ade

tifa

(201

0) Pai

Tsiou

ris

Hes

selin

g

Mac

hado

Ruh

wald

Oka

da

Pet

rucc

i (Nep

al)

Kas

sam

bira

Han

sted Le

e

Pet

rucc

i (Bra

zil)

Nicol

Oze

kinc

i*

Sha

nuab

e*

TST Positivity (%) QFT Positivity (%) TSPOT.TB Positivity (%)

*Proportion BCG vaccinated not reported. **TST positivity was computed using the TST cut-point used by authors of primary studies

In total, 20 comparisons (TST with TSPOT.TB or TST with QFT) were evaluated. Only 4 studies reported a

statistical difference in LTBI prevalence that was statistically significant. Three of these had study populations

that were 100% BCG vaccinated while one study reported a vaccination rate of around 75%. This study

evaluated both IGRAs against the TST, and found that the prevalence estimated by QFT was significantly lower

than that estimated by TST and by TSPOT.TB.

Figure 25 shows summary differences in prevalence of positive tests, with proportion BCG vaccinated along the

X-axis. Six comparisons resulted in a negative summary difference, while the remaining 13 comparisons (68%)

showed a positive difference indicating that IGRAs estimated a lower prevalence of LTBI compared with the TST

in these populations.


Page | 87

Figure 25. Summary differences in prevalence of positive tests against proportion BCG vaccinated

-40

-20

0

20

40

60

80

-0.1 0.1 0.3 0.5 0.7 0.9 1.1 1.3 1.5

Proportion BCG VaccinatedDif

fere

nce

in

est

ima

ted

pre

va

len

ce u

sin

g T

ST

an

d I

GR

As

(TS

T%

-IG

RA

%)

Difference (TST-QFT)

Difference (TST-TSPOT.TB)

Concordance between IGRA positivity and TST positivity varied from 18% in a hospital contact study to 93% in a cohort of household contacts aged 0-2 years. Five studies reported poor or fair agreement (kappa<0.4), 9 studies reported moderate agreement (kappa0.4-0.6) and 5 studies reported strong agreement (kappa>0.6). Among two studies that compared both TSPOT.TB and the QFT with TST results, one study reported very similar kappa values for both IGRAs (defined as kappa=0.52-0.54) while the other study found poor agreement for the TSPOT.TB and TST results (defined as kappa=0.12), yet moderate agreement between the QFT and TST results (defined as kappa=0.45).

3.5.7. Correlation between test positivity and exposure

All 16 studies captured the contact’s degree of exposure to an active TB case. Studies used a variety of variables and constructs to classify participants into exposure categories. In order to compare the association between exposure and test positivity across studies, exposure variables were classified into two broad categories: dichotomous exposure variables and variables representing an exposure gradient.

Test positivity and dichotomous exposure

Eight studies employed a dichotomised exposure variable. Six studies compared dichotomous exposure with cross-sectional test positivity rate in TST and IGRAs, one study employing up to 3 dichotomous exposure variables. The remaining two studies both had longitudinal designs and compared exposure (as a dichotomous variable) with TST or IGRA conversions post-exposure (Figure 26).


Page | 88

Figure 26. Association between test positivity and TB exposure, as a dichotomous variable

(Effect size estimates displayed are odds ratios)

Only one study (using a dichotomised contact score) reported a significant association between exposure and test positivity for all 3 tests (adj OR: TST: 3.83, TSPOT: 38.4, QFT: 14.94).

The Zambia unpublished study did not find a statistically significant difference between contacts of smear-positive versus contacts of smear-negative TB cases (preliminary data). One study found weak associations for either TST (adj OR=1.1) or QFT (adj OR=1.3) and the dichotomous exposure variable, but neither reached statistical significance. The study in children did not find a statistically significant difference in positivity rates between exposure groups for any tests.

In the study evaluating the association between exposure variables and either concordant positives (i.e. TST+/IGRA+) or discordant results, a strong association between TST-/IGRA+ and >1 month exposure was found (adj OR=7.2; 95%CI 1.7% - 29.3%), but no statistically significant association between exposure and TST+/IGRA-. The same study also found a statistically significant association between exposure and smear-positive status graded as 3+ (adj OR=2.8; 95%CI 1.3% - 6.1 %.)


Page | 89

Test positivity and gradient of exposure

Nine studies investigated an association between test positivity (TST and/or IGRA) and an exposure gradient (Table 18). The most common exposure gradient (used by three studies) was the so-called “Senegal/Gambia exposure gradient” categories, including different house, same house but different room, and same room. Four studies used exposure gradients based on the index case smear status. Four of the studies used groups with no TB exposure as comparison (community controls). The rest used different designs as outlined in Table 18.

Only one study reported a comparison of all three tests against an exposure gradient. TST positivity was associated with the exposure gradient and significant at each level. The association between IGRA positivity and the exposure gradient was only significant in the highest category of exposure (QFT adj OR 4.0; 95CI 1.4% - 11.4%; TSPOT.TB adj OR 6.6; 95CI 1.7% - 25.2%). The Zambia unpublished study used the same exposure gradient but found no significant association at any level of the exposure gradient for either TST or QFT.

Figures 28A (TST) and 28B (IGRA) display the ORs estimated by each study for the association between test positivity and exposure gradient.


Page | 90

Table 18. Results from studies using exposure gradients

Author, Year

Exposure level

QFT positivity

TSPOT.TB positivity

TST

positivity

Other associations

Adetifa, 2007 Different House adjOR= 1 - adjOR= 1 -

Same house, different room

adjOR=1.5 95% CI:0.6-3.6

- adjOR=2.4 95%CI:0.9-6.5

-

Same room adjOR=3.8 95%CI:1.2-12.5

- adjOR=4.8 95%CI: 1.3-17.1

-

Adetifa, 2010 Different House adjOR= 1 adjOR= 1 adjOR= 1 -

Same house, different room

adjOR=1.5 95%CI: 0.7-3.1

adjOR= 2.6 95%CI:0.9-7.1

adjOR=2.9 95%CI: 1.3-6.7

-

Same room adjOR= 4.0 95%CI: 1.4-11.4

adjOR= 6.6 95%CI: 1.7-25.2

adjOR=15 95%CI: 4.7-47.2

-

Nakaoka, 2006 Community Controls 4/39 (10%) 95%CI: 2.9-24.2

- - Association found between bacillary load of index case and the contact’s likelihood of testing QFT positive

(p=0.03)

Contacts of smear negative TB cases

8/81 (10%) 95%CI:4.4-18.5

- -

Contacts of smear positive TB cases

53/72 (74%) 95%CI:61.9-83.3

- -

Nicol, 2009 None: no contact - Increasing likelihood for positive TSPOT.TB and

TST Results with increasing exposure TSPOT.TB p=0.003

TST p=0.0081

Any: any contact with a case of TB

- OR=1.6 95%CI:0.7-3.3

OR=2.4 95%CI: 1.2-4.8

Adult: contact with an adult currently

receiving TB treatment

- - -

Household: contact with a patient with

- OR=2.4 95%CI: 1.3-4.6

OR=2.4 95%CI:1.4-4.2


Page | 91

active TB in the same household

Okada, 2007 Exposure to smear negative TB

adjOR=1 - adjOR=1 -

Exposure to smear grade 1+

adjOR=4.05 95%CI:1.04-15.75

- adjOR=1.5 95%CI: 0.56-4.04

-


adjOR=4.09 95%CI:1.0-16.66

- adjOR=2.25 95%CI:0.81-6.3

-


adjOR=9.72 95%CI:2.28-44.46

- adjOR=4.41 95%CI:1.46-13.29

-

Ozekinci, 2007 Group 4: Healthy & non-exposed

- 3/28 (10.7%)

95%CI: 2.3-28.2

15/28 (53.6%)

95%CI: 33.9-72.5

-

Group 3: Clinic and Lab Personnel

- 16/66 (24.2%)

95%CI:14.5-36.4

36/66 (54.5%)

95%CI: 41.8-66.9

Agreement 63.6% kappa= 0.305

P=0.006

Group 2: Household Contacts

- 16/56 (28.6%)

95%CI:17.3-42.2

27/56 (48%)

95%CI: 34.7-62

Agreement=53.6% Kappa= 0.011 p>0.05

Ruhwald, 2008 Community Controls 3/23 (13%) 95%CI: 2.8-33.6)

- 2/21 (10%)

95%CI: 1.21-30.4

Both QFT-GIT and TST show a significant trend

for increasing test positivity rate by

increasing smear grade among TB contacts

p<0.0001

Contacts of smear negative TB cases

3/38 (8%) 95%CI:1.7-21.4

- 7/37 (19%)

95%CI: 7.96-35.15

Contacts of smear positive TB cases

42/59 (71%) 95%CI:57.9-82)

- 24/53 (47%)

95%CI: 31.6-59.6

ZAMSTAR, 2010 Different house OR=1 - OR=1

Same bed OR=1.8 - OR=0.73


Page | 92

95%CI:0.63-2.19 95%CI:0.43-1.26

Same room OR=1.21 95%CI:0.53-2.77

- OR=0.92 95%CI:0.40-2.09

Same house OR=1.09 95%CI:0.62-1.90

- OR=0.77 95%CI:0.42-1.41

Unknown OR=1.12 95%CI:0.62-1.28

- OR=0.71 95%CI:0.39-1.28

Kasambira, 2010 Index case: Smear Positive (REF)

adjOR=1 - adjOR=1

Index case: Smear negative, culture pos TB

adjOR=0.84 (95%CI:0.09-7.8)

- adjOR=2.7 (95%CI:0.56-13)

Index case: clinical TB adjOR=3.9 (95%CI:0.67-23.5)

- --

Smear negative (REF) adjOR=1 - adjOR=1

Smear scanty -- - --

Smear 1+ adjOR=5.5 (95%CI:0.89-34.7)

- adjOR=7.9 (95%CI: 1.5-41)

Smear 2+ adjOR=8.7 (95%CI:1.2-62)

- adjOR=15.7 (95%CI:2.6-92)

Smear 3+ adjOR=11.4 (95%CI:1.8-72)

- adjOR=11.7 (95%CI:2.2-62)


Page | 93

Figure 27A. Association between TST positivity and exposure

gradient

(Effect size estimates displayed are odds ratios)

Figure 27B. Association between IGRA positivity and exposure gradient


Page | 94


Page | 95

Two studies used the same exposure gradient, and included a non-exposed comparison group (community controls). In one of these studies, contacts of smear-positive cases were more likely to be QFT positive than either community controls or contacts of smear-negative cases. In addition, an association was found between the smear grading of the index case and the contact’s likelihood of testing QFT positive (p=0.03). The other study had similar results for QFT but not for TST. Studies that did not use non-exposed comparison groups were unable to show similar trends.

The remaining studies all used unique exposure gradients, making these difficult to compare. The study which included very young children (0-2 yrs), found identical estimates of association between TSPOT.TB positivity and TST positivity in household contacts. One study grouped participants into healthy unexposed, clinical and laboratory personnel and household contacts but found no difference in TST or TSPOT.TB positivity across different exposure groups.

3.5.8 Concordance between test results in longitudinal contact studies

Three longitudinal studies were conducted in low and middle income countries which followed contacts over time and repeated TST and IGRA. All three studies evaluated QFT and TST but not the TSPOT.TB test (Table 19).

One small study followed contacts (n=25) approximately 8 weeks after nosocomial exposure: QFT and TST conversion rates in the less exposed groups ranged from 0-8.3% and 0-6.9% respectively, depending on how the exposure groups were characterized. QFT and TST conversion rates in the high TB exposure groups ranged from 0-25% and 0-10% respectively. Intimate contact (OR=1.94; 95%CI 0.2% - 21.1%) and face-to-face contact for more than 1 hour (OR=9.2; 95CI 0.7% - 100%22.38) tended to be associated with a higher risk of QFT conversion, but this did not reach statistical significance.

The second study included an analysis of household contact in India over a 1-year period. QFT conversion rates of 21.2 % and TST conversion rates of 13.8% (6mm increase over baseline) and 7.5% (10mm increase over baseline) were observed. This study also assessed the incidence of QFT reversions, and found an overall rate of 6.4% over 1 year; this rate was higher (17-20%) when restricted to those with quantitative baseline QFT results (IFN-g <3.0 IU/ml). Associations between test conversions and exposure were not examined, however, 83% agreement between TST and QFT conversions (1 year post-exposure) was found, with a kappa=0.42 (0.17-0.68).

The third study (unpublished, South Africa) followed children exclusively. Conversion rates were calculated for a 6-month follow-up period. In baseline negatives, 18.8% (22/117) of QFT conversions were observed while TST conversions were found in 11% (13/118) of baseline TST negatives. This difference was statistically significant (p=0.03). While no exposure variables were associated with TST conversions, an association between exposure and QFT conversions (adjOR=0.06 for index case smear status 3+; 95CI 0.08-0.49) was seen.


Page | 96


Page | 97

Table 19. TST and QFT conversions in contact studies in low- and middle-income countries Author, Year Type of exposure QFT

conversion (%)

TST conversion

(%)

QFT conversion OR (95CI)

TST conversion OR (95%CI)

Concordance

Lee, 2007 Intimate Exposure 12.5 8.3 1.94 (0.18-21.12)

- -

No intimate exposure 6.7 0 (Ref) -

-

Contact time (>8h) 15 10 - - -

Contact time (<8h) 0 0 - - -

Face to face contact (>1h) 25 0 9.2 (0.69-22.38)

- -

Face to face contact (<1h) 3.5 6.9 (Ref) - -

Same room (>8h) 0 0 - - -

Same room (<8h) 8.3 5.6 - - -

Pai, 2009 Household contacts 21.2 (+6mm) 13.8

(+10mm) 7.5

- - kappa=0.42

Kasambira, 2010 Household contacts (≥6months-≤16 yrs)

22/117 (18.8%)

13/118 (11%)

p=0.03

Index case smear status 3+ adjOR=0.06 (0.008-0.49)

No association


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3.5.9. Indeterminate IGRA results

Rates of indeterminate results varied across studies. 11/15 (80%) of studies reported indeterminate rates below 5%. In the two studies that evaluated both IGRAs higher indeterminate rates were reported with the QFT test than the TSPOT.TB (data not shown).

3.5.10 Strengths & limitations of the evidence base

Due to heterogeneity in study designs and outcomes assessed in each study, it was not appropriate to pool the data. The majority of studies were cross-sectional and looked at concordance between TST and IGRAs. Studies that assessed associations between exposure and test positivity used different categorisation of exposure variables, making it difficult to compare results across studies.


The majority of studies showed comparable LTBI prevalence by TST or IGRA in contacts;

The most commonly observed discordance was of the TST+/IGRA- type;

Both IGRAs and the TST seem to show positive associations with higher levels of exposure in cross-sectional studies, but the strength of the association (effect) varied across studies;

IGRAs appear to be dynamic assays with frequent conversions and reversions;

Both IGRAs and TST seem to have similar and modest predictive value;


The GRADE evidence profiles are provided in Table 20. Based on these assessments, the Expert Group

concluded that the quality of evidence for use of IGRAS for LTBI screening in contact and outbreak

investigations was very low and recommended that these tests should not be used as a replacement for TST,

neither in adults or children investigated as close contacts of patients with confirmed active TB.




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Table 20. GRADE evidence profile: Performance of IGRAs for the diagnosis of LTBI in contacts of active TB in low-and middle-income countries. No of Participants (Studies)


1

Importance

A. Efficacy of preventive therapy based on IGRA test results

No Studies Critical (7-9)

B. Predictive value of IGRA for active TB

9 studies: Covered in Predictive SR: Rangaka et al Critical (7-9)

C. Outcome: Correlation between IGRAs and different gradients of TB exposure (ordinal, continuous, etc.)

3,868 (9)A1

Cross-sectional

Serious A2

(-1) No Serious

indirectnessA3

SeriousA4

(-1)

No serious imprecision

A5

Likely A6

Low

Critical (7-9)

D. Outcome: Correlation between IGRAs and TB exposure as a dichotomous variable

3,145 (6) B1


Serious B2

(-1) No Serious

indirectnessB3

Serious B4

(-1) Serious

B5

(-1) Likely

B6 Very Low

Critical (7-9)

E. Outcome: Correlation between IGRA conversions and TB exposure

309 (2) C1

Longitudinal Serious

C2

(-1) No Serious

indirectnessC3

Very SeriousC4

(-2) Serious

C5

(-1) Likely

C6 Very Low

Critical (7-9)

F. Outcome: Sensitivity for active TB (as a surrogate reference standard for LTBI)

No Studies Important (4-6)

G. Outcome: Concordance with tuberculin skin test (TST)

5,080 (16)D1


Serious D2

(-1) Very Serious

D3

(-2) Very Serious

D4

(-2) Serious

D5

(-1) Likely

D6 Very Low

Important

(4-6)


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Footnotes:

1Quality of evidence was rated as high (no points subtracted), moderate (1 point subtracted), low (2 points subtracted), or very low (>2 points subtracted) based on five criteria: imitations,

indirectness, inconsistency, imprecision, and publication bias. For each outcome, the quality of evidence started at high when there were randomized controlled trials or high quality observational studies (cross-sectional or cohort studies with diagnostic uncertainty and direct comparison of test results with culture) and at moderate when these types of studies were absent. One point was subtracted when there was a serious issue identified or two points when there was a very serious issue identified in any of the criteria used to judge the quality of evidence.

A1 9 studies were included: 1 study evaluated both TSPOT.TB and QFT-GIT, 2 studies evaluated TSPOT.TB, the 6 remaining studies evaluated QFT-GIT(n=5) or QFT-G(n=1).

A22 out of 9 studies were unpublished and quality indicators could not be assessed; remaining study populations were considered to be representative, however, only 1 of the remaining 7 studies

reported that assessment of test results was performed blinded to other test results. Only 2/7 reported the blood draw had been performed prior to the TST.

A333% (3/9) studies were done in low-income settings and the remaining 6 studies were done in middle-income settings. Some indirectness in the choice of reference standard was observed.

A4 Serious heterogeneity in characterization of exposure gradient (some based on index case’s smear status, some based on sleeping proximity, etc.) and in estimated effect.

A5 Majority of studies had 200-300 participants, smallest study n=120. Estimated 95%CIs were relatively tight.

A6 Data included in the review did not allow for formal assessment of publication bias using methods such as funnel plots or regression tests. Therefore, publication bias could not be ruled out.

Although no points were deducted, it was assumed that some degree of publication bias is likely because: 1) literature on IGRAs is rapidly exploding and currently unpublished studies may come out in future (although an attempt was made to include unpublished studies, despite not being comprehensive); 2) there are anecdotal examples of unpublished negative studies on IGRAs; 3) because a sizeable proportion of IGRA studies have some level of industry involvement or support, the risk of unpublished negative studies (or delayed publication of negative studies) is not trivial.

B16 studies were identified: 1 study evaluated both TSPOT.TB and QFT-G, while 1 study evaluated TSPOT.TB. The remaining 4 studies all evaluated QFT-GIT.

B2Only the 4 published studies could be assessed for quality, 50% reported on timing of blood draw prior to TST, 50% reported blinding had been done for assessment of test results and 50% reported

industry involvement.

B3All studies, except one done in low-income setting were done in upper-middle income settings. Some indirectness in the choice of reference standard was noted.

B4 Serious heterogeneity in characterization of exposure gradient (some based on index case’s smear status, some based on sleeping proximity , etc.) and in estimated effect.

B5 All but one large study (n=2211) had between 82-301 participants. Studies estimated wide 95%CI, and majority were not significant.

B6 Data included in the review did not allow for formal assessment of publication bias using methods such as funnel plots or regression tests. Therefore, publication bias could not be ruled out.

Although no points were deducted, it was assumed some degree of publication bias was likely because: 1) literature on IGRAs is rapidly exploding and currently unpublished studies may come out in future (although an attempt was made to include unpublished studies, despite not being comprehensive); 2) there are anecdotal examples of unpublished negative studies on IGRAs; 3) because a sizeable proportion of IGRA studies have some level of industry involvement or support, the risk of unpublished negative studies (or delayed publication of negative studies) is not trivial.

C1 2 studies were included; both studies evaluated the QFT, one study using the QFT-GIT and the other the QFT-G.


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C21 study was unpublished and hence not suitable for quality assessment, the other study was a longitudinal study that followed HCWs after a nosocomial infection. Population was representative,

blood draw was done prior to TST, and there was no industry involvement, however, blinding was not reported.

C3 Both studies were done in Upper middle income settings, however one was a nosocomial outbreak involving health care workers and may not be generalizeable to other contact settings including

household contacts, especially in low income settings. While we did not downgrade for reference standard, we acknowledge there is some indirectness in the choice of reference standard.

C4 Serious heterogeneity between estimated ORs for exposure and conversions, one study shows an positive association between conversions and exposure, while the other shows a significant

protective effect of exposure for conversions.

C595% CIs are tight and significant for the large unpublished (n=2211), however, CIs range from 0.18-21.12 and 0.69-122.38 for the smaller hospital outbreak study (n=39)

C6 Data included did not allow for formal assessment of publication bias using methods such as funnel plots or regression tests. Therefore, publication bias cannot be ruled out. Although we did not

deduct points, we assumed some degree of publication bias is likely because: 1) literature on IGRAs is rapidly exploding and currently unpublished studies may come out in future (although we made an attempt to include unpublished studies, our attempt was not comprehensive); 2) there are anecdotal examples of unpublished negative studies on IGRAs; 3) because a sizeable proportion of IGRA studies have some level of industry involvement or support, the risk of unpublished negative studies (or delayed publication of negative studies) is not trivial.

D12 studies included both IGRAs, 3 studies evaluated only TSPOT.TB, while the rest evaluated a version of the QFT.

D211/14 studies did not report on whether personnel assessing test results had been blinded to previous test results or reference standard, and 5/14 studies reported industry involvement.

D3Studies were conducted in low and middle income settings. TB exposure gradient does not necessarily classify the target condition (LTBI) correctly.

D447% of studies showed moderate agreement, while 26.5% showed poor agreement and 26.5% fair agreement. In 68% of comparisons, TST estimated a higher prevalence while in the remaining 32%

IGRAs estimated a higher prevalence of LTBI.

D5Due to heterogeneity in effect estimates concordance could not be pooled. However, effects estimated for individuals studies were frequently not significant.

D6 Data included did not allow for formal assessment of publication bias using methods such as funnel plots or regression tests. Therefore, publication bias cannot be ruled out. Although points were

not deducted, a degree of publication bias is likely because: 1) literature on IGRAs is rapidly exploding and currently unpublished studies may come out in future (although we made an attempt to include unpublished studies, our attempt was not comprehensive); 2) there are anecdotal examples of unpublished negative studies on IGRAs; 3) because a sizeable proportion of IGRA studies have some level of industry involvement or support, the risk of unpublished negative studies (or delayed publication of negative studies) is not trivial.

The predictive value of IGRAs for incident active TB

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3.6 The predictive value of IGRAs for incident active TB


Primary objectives

To assess whether IGRAs can prospectively predict the development of active TB (incident TB) amongst

individuals without active TB disease at first assessment;

To determine whether IGRA predictive (prognostic) ability is significantly higher than that for the TST.

Secondary objectives

To assess the variability in IGRA-positive and -negative TB rates of progression by demographic and

clinical risk factors for TB: provision of IPT, age strata (adult or children), HIV infection, BCG status;

To determine the influence of immunological phenotypes of discordant and concordant TST/IGRA pairs

at baseline on subsequent TB rates;

To determine the existence of a gradient relationship between quantitative IFN-gamma response levels

and rates of progression to TB disease;

To assess the variability in the rates of TB in IGRA-positive individuals with TST (negative and positive)

results who were treated with IPT. Reference standards

As there was no data at the highest level of the hierarchy of evidence, the focus was on rates of incident

active TB disease in individuals with positive and negative IGRA results at baseline and how they compare

to those with positive and negative baseline TST results

Primary outcomes

Crude incidence rates of disease progression, analysed by relevant strata (eg. IGRA-positive and -

negative, IGRA/TST discordant and concordant pairs, IGRA quantitative levels);

Incidence rate ratios (IRR) for disease progression in IGRA-positive versus IGRA-negative individuals

(and likewise for the TST);

When exploring differences in the predictive ability of IGRA compared to the TST, rate ratios for TB in test

positives vs. test negatives were computed and pooled, where appropriate, for studies that performed both

TST and IGRA.


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Definitions

Sensitivity: The probability that a baseline IGRA test is positive amongst those who ultimately developed

active TB during follow up;

Specificity: The probability that a baseline IGRA test is negative in those that did not subsequently develop

active TB.

Sensitivity and specificity were regarded as surrogates of patient-relevant outcomes important for

assessing the frequency and impact of either a false-negative or false-positive IGRA result at baseline: A

false-positive test result may result in unnecessary preventive therapy in an individual who would not have

progressed to TB disease, while a false-negative result would mean progression to active TB disease that

could have been prevented.


Six studies conducted in low- and middle-income countries were identified. Of these, three were conducted

in low-income countries (The Gambia, Senegal, Zambia) and three were done in middle-income countries

(Turkey, China, South Africa). Three of the six studies (n=7,392) evaluated commercial IGRAs. Two studies

(South Africa, Zambia) used the most recent QuantiFERON Gold In Tube technology while the third (China)

evaluated the T-Spot.TB assay.

3.6.3 Data analysis

Data was extracted from included articles according to study design, participants, country, period of

recruitment, proportion BCG vaccinated, IGRA method (assay used, test version, cut-off point used, etc.),

TST method (PPD dose, cut-point used, etc.). Outcome data included baseline TST and IGRA positivity,

IGRA/TST concordance/discordance and rates of progression to active TB.


Studies included were those which enrolled adults or children without TB at baseline, regardless of HIV

infection status. The studies were of longitudinal design (prospective or retrospective cohorts) and included

any period of follow-up using either active or passive strategies.

The populations included in the studies were all different but all studies followed-up cohorts of groups

known to be at high risk of TB progression. The China study recruited an older (mean age 60 years), all-

male, high-risk TB group with confirmed silicosis; the South Africa study recruited school-going adolescents

between 12 and 18 years. The Zambia study included TB case-contacts (15 - 65+years), with 37% of the 721

individuals in the cohort being HIV infected. None of the other two studies included HIV infected

individuals. Over 80% of the China and South Africa study cohorts completed follow-up (information not

available for the Zambia study).

Isoniazid preventive therapy (IPT) was only provided in the China cohort (33% of 203 TST-positives).

3.6.5 Study quality

IGRA predictive value studies are prospective studies that are not focused on conventional diagnostic test

accuracy estimates of sensitivity and specificity, or single unadjusted measures of positive and negative

predictive values. A modified version of the Newcastle-Ottawa Quality Assessment Scale for cohort studies

was therefore used.


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Specific modifications were made to the selection and outcome items, in particular to ascertainment or verification of the reference standard for active TB. Although microbiological determination of TB is regarded as the gold standard, not all studies used conventional microbiology to assess outcome. Possible verification bias was therefore considered to ascertain whether some exposure groups were more likely to have been assessed differently. Studies from countries that have incorporated IGRA use into their guidelines for TB are likely to demonstrate a greater association, and therefore, better predictive ability of IGRA with incident active TB disease; thus, studies were assessed to determine whether respective countries had already included IGRA in their guidelines for identifying latent TB infection and/or active TB disease. The incorporation bias item was drawn from the QUADAS tool.

Overall, included studies varied in quality particularly with regard to the comparability (adjustments made

to effect measures) and outcome (ascertainment, losses to follow-up, reporting) components of the

modified NOS. Only the China study reported microbiological confirmation (around 80%) of at least 50% of

the diagnosed incident TB cases. The South Africa study incorporated IGRA results in their reference

standard for active TB.

3.6.6 Incidence rates of TB during follow-up

Overall incidence rates (IR) of TB were 22.5/1000 person years (PY) and 20.7/1000 PY for the China and

Zambia studies, respectively. The South Africa study did not report overall TB rates but did provide results

stratified by IGRA exposure status. Pooled IR of TB appeared to be higher in IGRA-positive individuals

(IR=16.47; 95CI 11.2-21.7; I2=98%, p<0.0001) vs. IGRA-negatives (IR=2.85; 95CI 0.9-4.8; Figure29). However,

even in those with positive IGRA results, the vast majority of individuals did not progress to TB disease

during follow-up. Sub-groups analyses were not performed due to the small number of studies.


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Figure 28. Crude TB incidence rates stratified by IGRA status


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3.6.7 The association between IGRA and incident active TB

Incident rate ratios

Pooled estimates should be interpreted with caution as there were only 3 studies per stratum. The strength

of the association between IGRA positivity and incident TB was moderate, indicated by a pooled incidence

rate ratio (IRR) of around 3, failing to reach significance as indicated by wide confidence intervals (95CI 0.7-

5.6; I2 for pooled estimate=0%, p=0.912) (Figure 29).

Figure 29. Crude, unadjusted TB incidence rate ratios for IGRA-positives vs. IGRA-negatives

3.6.8 The predictive value of IGRA compared with TST

All three studies provided incidence rate ratios of TB stratified by IGRA as well as TST status at baseline. The

association with subsequent incident TB in test-positive individuals compared to test-negatives appears

higher for IGRA than for TST; however, this was not statistically significant as indicated by overlapping

confidence intervals ( IGRA: IRR=3.24; 95CI 0.62-5.85; I2=0%; p=0.90; TST: IRR=2.28; 95CI 0.83-3.73; (Figure

10).


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Figure 10. Crude, unadjusted incidence rate ratios for IGRAs compared to the TST

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3.6.9 The influence of discordant- concordant TST/IGRA pairs at baseline on subsequent TB rates

Evaluating discordant results may represent the best way to assess whether IGRAs perform better than the

TST in predicting risk of incident TB disease. TST+/IGRA- results are mainly thought to indicate remote LTBI.

By contrast, TST-/IGRA+ may represent more recently acquired infection that may either subsequently clear

or progress to active disease.

The Zambia and South Africa studies (combined N=5,861) explored rates of TB in paired concordant and

discordant TST/IGRA results (Table 21). Double-positive results (TST-positive/IGRA-positive) seemed to yield

higher rates of TB during follow-up compared to double-negative results (TST-negative/IGRA-negative).

The Zambia study reported higher rates in the discordant pair where IGRA was the positive test compared

to when TST was the positive test (incident TB rate 29.7/1000PY; 95CI 13.4 – 66.2). In contrast the South

Africa study reported marginally higher rates in IGRA-negative/TST-positive discordant pairs (incident TB

rate 3.3/1000PY; 95CI 0.4-12.0) than in IGRA-positive/TST-negative pairs (incident TB 1.8/1000PY; 95CI 0.4-

5.4). However, these differences are not significant as the confidence intervals are wide and overlap.

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Table 21. Discordant-concordant TST/IGRA pairs and incidence rates of TB

Country Phenotype n/N PY IR per 1000PY 95% CI

Zambia IGRA+/TST- 6/191 201.7 29.7 13.36-66.20

10mmTST IGRA-/TST+ 0/42 44.6 0 -

14pg/ml IGRA+/TST+ 6/173 201.1 29.8 13.4-66.41

IGRA-/TST- 0/211 224.9 0 -

S. Africa IGRA+/TST- 3/714 1628 1.8 0.4-5.4

10mm TST IGRA-/TST+ 2/259 601 3.3 0.4-12.0

14pg/ml IGRA+/TST+ 35/1955 5250 8 4.6-9.3

IGRA-/TST- 10/2316 4508 2.1 1.1-4.1

3.6.10 Gradient between rates of TB and quantitative IGRA levels

It has been proposed that the risk of subsequently developing TB following testing may vary according to

the levels of IFN-gamma produced in response to RD1-antigens. In turn, the levels of IFN-gamma produced

may depend on the mycobacterial burden or IFN-gamma may reflect active replicating bacilli. In case-

contact studies the length or intensity of exposure may therefore correlate with the level of IFN-gamma

produced.

The Zambia study (N=721) explored this hypothesis, suggesting that there was no exposure-gradient

relationship between quantitative baseline IGRA levels and rates of subsequent TB. Paradoxically, TB rates

appeared highest in the lowest IGRA quartile (0.35-0.64 IU/ml) at 73.8/1000PY (95CI 23.8-228.94). High

background TB prevalence, (ie. higher infection pressure and higher re-infection possibility), high

background HIV prevalence and the high proportion of HIV-infected individuals in the follow-up cohort may

explain these results; however, comparisons across the different IGRA levels were not statistically

significant.

3.6.11 Patient relevant outcomes

The diagnostic accuracy estimates of sensitivity and specificity are surrogates of patient-relevant outcomes

important for assessing the frequency and impact of either a false-negative or false-positive IGRA result at

baseline in respective cohorts: For example, a false-positive result may result in IPT prescription for several

months and although safe is not without adverse effects, notably clinical hepatitis; A false-negative result

will result in no IPT being provided and the individual exposed to an increased risk of developing active TB

in the future.

As only three studies were available, summary ROC statistics could not be derived; therefore, a description

of test accuracy estimates per individual study is provided: IGRA sensitivity for incident TB was 88% (95CI

64% - 99%) in China (T-SPOT.TB), 75% (95CI 48% - 93%) in Zambia (QFT-GIT) and 75% (95CI 61% - 86%) in

South Africa. Specificity was low across the three studies at 35% (95CI 30% - 41%), 50% (95CI 46% - 54%)

and 49% (95CI 48% - 51%) respectively. This means that more than 50% of individuals would unnecessarily

receive IPT based on a positive IGRA result alone.

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TST sensitivity for incident TB was similar at 76% (95CI 50% - 93%) and 73% (95CI 59% - 84%) for the China

and South Africa studies, respectively. Specificity was low at 35% (95CI 29% -41%) in China and 58% (95CI

57% - 58%) in South Africa. This means that between 40% and 60% of individuals would unnecessarily

receive IPT based on a positive TST alone. In the Zambia study results were different - TST sensitivity for

subsequent TB disease was low at 44% (95CI 20% - 70%) while specificity was higher than in the other two

studies (67%; 95CI 64% - 71%). The Zambia study acknowledged logistical issues at the clinical sites that

possibly affected TST results.

3.6.12 The predictive value of serial testing

This could not be assessed as all three studies performed single time-point IGRA testing.


Included studies vary in quality, particularly with regard to comparability (adjustments made to

effect measures) and outcome (ascertainment of incident TB, losses to follow-up, and reporting of

incidence rates vs. cumulative incidence);

A reference standard that is not independent of the index test introduces differential

ascertainment bias and is likely to complicate studies, especially those from countries where IGRAs

have been adopted as part of national TB work-up algorithms. Prognostic studies of IGRA

conducted in such countries should give full discussions of the extent of this and also mention how

that was considered in final analyses, if at all.

The vast majority of individuals (>95%) with a positive IGRA results did not progress to active TB

disease during follow-up, although a modest and statistically insignificant increase in incidence

rates of TB in IGRA- positives compared to IGRA-negatives has been observed;

Both IGRAs and the TST appear to have only modest predictive value and do not help identify those

who are at highest risk of progression to disease. Patient relevant outcomes based on sensitivity

and specificity appear comparable between the two tests.



Group concluded that the quality of evidence for the predictive value of IGRAS was very low and

recommended that these assays should not be used to identify individuals at risk of active TB disease in

low- and middle-income countries.



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Table 22. GRADE Evidence Profile: Predictive value of commercial IGRA for incident active TB in Low and Middle-Income Countries No of Participants (Studies)

Study design Limitations Indirectness Inconsistency Imprecision Publication Bias

Quality of Evidence (GRADE)

1

Importance

A. Outcome: Efficacy of preventive therapy based on IGRA results


B. Outcome: Prospective predictive value of IGRA for the development of active incident TB? (Do IGRA positive results have a stronger association with subsequent development of active TB compared to IGRA negative results?)

7,392 (3)

B1

Cohort studies Serious (-1) B2

Serious (-1) B3

No serious

inconsistency B4

Very Serious (-2)

B5 Likely

6

Very low

Critical (7-9)

C. Outcome: Predictive value of IGRA for the development of active incident TB compared to the TST (Are IGRAs (positive vs. negative) have a stronger statistical association with subsequent active TB than the TST (positive vs. negative)?

7,392 (3)

C1

Cohort studies Serious (-1) C2

Serious (-1) C3

No serious

inconsistencyC4

Very Serious (-2)

C5 Likely

C6

Very low

Critical (7-9)

D. Outcome: Predictive value of IGRA for subsequent TB when IGRA are evaluated as part of a multivariable clinical algorithm for predicting TB (Additive value of IGRA)

No studies Important (4-6)

E. Outcome: Quantitative IGRA levels and subsequent rates of TB

721 (1)

E1

Cohort of TB case-contacts

Serious (-1) E2

Serious (-1) E3

Serious (-1) E4

Very Serious (-2) E5

Likely E6

Very low

Important (4-6)

F. Outcome: Immunological phenotypes of discordant-concordant TST/IGRA pairs and subsequent rates of TB

5,861 (2)

F1

Cohort studies Serious (-1) F2

Serious (-1) F3

Serious (-1) F4

Very Serious (-2) F5

Likely F6

Very low

Important (4-6)

G. Outcome: Sensitivity, Specificity, False positive rates etc for active TB (as surrogates of patient relevant outcomes)

7,392 (3)G1

Cohort studies Serious (-1) G2

Serious (-1) G3

Serious (-1) G4

Very Serious (-2) G5

Likely G6

Very low

Important (4-6)

H. Outcome: Utility of repeated or serial IGRA results for predicting subsequent incident active TB

No studies

Important (4-6)

Footnotes

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1 Quality of evidence was rated as high (no points subtracted), moderate (1 point subtracted), low (2 points subtracted), or very low (>2 points subtracted) based on five criteria: study limitations,

indirectness of evidence, inconsistency in results across studies, imprecision in summary estimates, and likelihood of publication bias. For each outcome, the quality of evidence started at high when there were randomized controlled trials or high quality observational studies and at moderate when these types of studies were absent. We then subtracted one point when there was a serious issue identified or two points when there was a very serious issue identified in any of the criteria used to judge the quality of evidence. B1

3 studies were eligible and thus included in the analysis; 1 published (China) and 2 unpublished (Zambia and South Africa). (N refers to numbers that entered follow-up)

B2 Based on the Newcastle-Ottawa scale, study samples were considered to be representative of specific groups of interest (i.e., silicosis patients (China), case-contacts (Zambia), adolescent school-

goers) within the population and IGRA exposure groups were drawn from the same sample and therefore unlikely to introduce any bias. However, studies varied with regard to the comparability (adjustments made to effect measures) and outcome (ascertainment, losses to follow-up, reporting) components of the modified NOS. Lack of proper ascertainment of the TB outcome is considered to be the most serious of limitations. A point is deducted. B3

The results of the studies could be generalized for the specific country/region and for those specific groups of interest. However, the small number of studies warrants caution; a point is deducted for indirectness. B4

All 3 studies showed similar results and with very little heterogeneity in the pooled incidence rate ratio (I2=0%, p=0.912). No points were deducted.

B5

The number of incident TB cases was small in all studies and the rates of TB fairly moderate; confidence intervals for relative risk estimates were wide (precision > +/- 20%). This is a very serious limitation. Two points are deducted. B6

Data included did not allow for formal assessment of publication bias using methods such as funnel plots or regression tests. Therefore, publication bias cannot be ruled out. Although no points were deducted, a degree of publication bias is likely because: 1) literature on IGRAs is rapidly exploding and currently unpublished studies may come out in future (although we made an attempt to include unpublished studies, our attempt was not comprehensive; we are aware of at least one unpublished study that was not assessed for this review); 2) there are anecdotal examples of unpublished negative studies on IGRAs; and 3) because a sizeable proportion of IGRA studies have some level of industry involvement or support, the risk of unpublished negative studies (or delayed publication of negative studies) is not trivial. C1

All three studies provided incidence rates of TB stratified by IGRA as well as TST status at baseline. (N refers to numbers that entered follow-up) C2

Serious limitations include lack of proper ascertainment of the TB outcome by smear and/culture, IGRA incorporated in the methods to diagnose TB (South Africa) and lack of adjustment of all confounders. A point is deducted. C3

The results of the studies could be generalized for the specific country/region and for those specific groups of interest. However, the small number of studies warrants caution; a point is deducted for indirectness. C4

The two tests perform comparably and any differences are not statistically significant as the 95% confidence intervals for the pooled IRRs overlap and there is no heterogeneity in the pooled estimates for either test (IGRA+: IRR=3.2, I

2=0%, p=0.899 and TST+: IRR=2.3, I

2=0%, p=0.383). No points deducted.

C5 The confidence intervals of the pooled IRRs are wide (precision > +/- 20%). This is a very serious limitation. Two points are deducted.

C6 Publication bias was not formally assessed, but is deemed likely. See

B6.

E1

Only the Zambian study examined if there was an exposure-gradient relationship between baseline quantitative IGRA levels and subsequent rates of TB in those levels. (N refers to numbers included in this stratified analysis) E2

Lack of proper ascertainment of the TB outcome by smear/culture for both studies. The Zambian study is unpublished and only an interim report was available, so quality could not be fully assessed. A point is deducted. E3

There is only one study. There is serious indirectness. A point is deducted. E4

There is only one study; inconsistency cannot be assessed. A point is deducted. E5

The 95% confidence intervals per IGRA stratum were extremely wide (precision > +/- 20%). Two points are deducted. E6

Publication bias was not formally assessed, but is deemed likely. See B6

. F1

The Zambia and South Africa studies further explored rates for TB in paired concordant and discordant TST/IGRA results. (N refers to number included in this stratified analysis)

Page | 113

F2 Serious limitations include lack of proper ascertainment of the TB outcome by smear and/culture, IGRA incorporated in the methods to diagnose TB (South Africa) and lack of adjustment of all

confounders. A point is deducted F3

Although results may be generalizable to similar L/MIC, there are only two studies. A point is deducted. F4

Rates of TB during follow-up may be higher in those with double positive TST+/IGRA+ results than in those with double negative results. Both studies seem to suggest this. However, contrasting results are seen with regard to discordant pairs. Pooled estimates were not derived. The inconsistency in results is deemed serious; a point is deducted. F5

Observed 95% confidence intervals around the rates per strata are wide (precision > +/- 20%). F6

Publication bias was not formally assessed, but is deemed likely. See B6. G1

All 3 studies were included in this evaluation of patient-relevant outcomes. The diagnostic accuracy estimates of sensitivity and specificity etc are surrogates of patient-relevant outcomes important for assessing the frequency and impact of either a false negative or false positive IGRA result at baseline. A falsely positive outcome may result in possible isoniazid preventive therapy (IPT) prescription for a period of 6-9months, depending on country guidelines. IPT, although safe, is not without serious adverse effects, notably, clinical hepatitis and the increased possibility of drug resistance in the future. Whilst a falsely negative result may result in no IPT being provided and the individual exposed to at least a 2-fold risk of developing TB in the future. G2

Serious limitations include lack of proper ascertainment of the TB outcome by smear and/culture, IGRA incorporated in the methods to diagnose TB and lack of adjustment of all confounders for most studies. A point is deducted G3

Although results may be generalizable to similar L/MIC, there are only three studies. A point is deducted. G4

There is heterogeneity in individual studies’ test accuracy estimates (e.g. specificity/false positive rates). A point is deducted.

G5 The summary estimates of sensitivity and specificity are moderate and the confidence intervals are wide (precision > +/- 20%). Two points are deducted.

G6 Publication bias was not formally assessed, but is deemed likely. See

B6.

Table 23. GRADE Summary of findings: Predictive value of commercial IGRA for incident active TB in low and middle-income Countries Review question: What is the predictive value of interferon-gamma release assays for incident active tuberculosis disease in low and middle-income countries? Patients/population: Studies of adults or children without TB at baseline and regardless of HIV infection status. Setting: Community-based cohort in a high-burden country, high-risk for TB individuals attending outpatients clinics and school-going adolescents residing in a high-burden country Index test: Latest Commercial IGRA (QuantiFERON Gold In Tube and T-Spot.TB) Importance: The predictive value of IGRAs for subsequent incident TB is uncertain. Longitudinal studies on the predictive (prognostic) value of a positive IGRA are emerging. Data from these studies provide the initial evidence to refute or support the use of IGRAs in targeting chemoprophylaxis for IGRA-positive individuals. Reference standard: Development of TB. See hierarchy of reference standards. Studies: Any longitudinal study design (e.g. prospective or retrospective cohort), low and middle-income countries. Follow-up (of any length) should be described. This can either be active or passive follow-up.

Outcome N (No. of studies)

Principal Findings What do these findings mean?

Quality of Evidence

Importance

Efficacy of preventive therapy based on IGRA results


Prospective predictive value of IGRA for the development of active incident TB? (Do IGRA positive results have a stronger

7,392 (3) 1) IGRA positives results appear to have a moderate but higher statistical association with incident TB compared to IGRA negatives, pooled IRR=3.2 (95% CI 0.74-5.64), I2=0%, p=0.91. This estimate is not statistically significant- the

Moderate increase in incidence rates of TB in IGRA positives compared to IGRA negatives. This

Very low

Critical

(7-9)

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association with subsequent development of active TB compared to IGRA negative results?)

confidence interval includes the null. Furthermore, the small number of studies, the heterogeneity of populations studied all warrants caution when interpreting the pooled results. Despite the lack of evidence for statistical heterogeneity.

2) IGRA positives results appear to have higher rates of incident TB than IGRA negatives. A pooled IR (IGRA+)=16.5 (95% CI 11.24-21.7), I

2=98%, p<0.0001 and

IR (IGRA-)=2.85 (95% CI 0.86-4.84), I2=35%, p=0.217. The 95% CI do not overlap suggesting the difference may be significant. However, this is based on just three studies with different populations. The pooled results should be interpreted with caution; there is low-high statistical heterogeneity.

translates to moderate risk of progression. There are too few studies to conclude this with certainty.

However, even in those with positive IGRA results, the vast majority of individuals did not progress to TB disease during follow-up.

Predictive value of IGRA for the development of active incident TB compared to the TST (Do IGRAs (positive vs. negative) have a stronger statistical association with subsequent active TB than the TST (positive vs. negative)?

7,392 (3)

1) IGRA+: Pooled IRR=3.24 (0.62-4.69); I2=0%, p=0.90

2) TST+: Pooled IRR=2.3 (0.83-3.73); I2=0%, p=0.38

The derived estimates are not statistically significant; the confidence intervals include the null. The pooled estimates should also be interpreted cautiously: there are only three studies; heterogeneous populations and study methods

IGRA+ and TST+ may have a similar strength of association with subsequent TB compared to test negative individuals.

Very low

Critical

(7-9)

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Predictive value of IGRA for subsequent TB when IGRA are evaluated as part of a multivariable clinical algorithm for predicting TB (Additive value of IGRA)

No studies Important

(4-6)

Quantitative IGRA levels and subsequent rates of TB

721 (1) No pooled estimates: there is only one study

It suggests no exposure-gradient relationship between quantitative IGRA levels and rates of subsequent TB. Rates appeared highest in the lowest IGRA quartile, 0.35-0.64 IU/ml at 73.8/1000PY (23.8-228.94), and not at subsequent higher strata, 0.65-3.94 IU/ml at 30.1 (12.5-72.4), 3.95-10 IU/ml at 0 rate per/1000PY and the highest IGRA quartile of >10 IU/ml at 50/1000PY (18.8-133.1). However, comparisons across the strata are not statistically significant, as confidence intervals overlap and results should be interpreted with caution.

Inconclusive results. Number of studies assessed is too small.

Very low

Important

(4-6)

Immunological phenotypes of discordant-concordant TST/IGRA pairs and subsequent rates of TB

5,861 (2) No pooled estimates.

Rates of TB during follow-up may be higher in those with double positive TST+/IGRA+ results than in those with double negative results.

The Zambia study reported higher rates in the discordant pair where IGRA was the positive tests compared to when TST was the positive tests, 29.7/1000PY (13.4 – 66.2) and 0 for IGRA+/TST- and IGRA-/TST+, respectively. By contrast the South African study reported marginally higher rates in IGRA-/TST+ of 3.3/1000PY (0.4-12.0) than in IGRA+/TST- of

Inconclusive results. Numbers of studies is too small and/or the rate of TB observed per strata too low.

Very low

Important

(4-6)

Page | 116

1.8/1000PY (0.4-5.4). However, these differences are not significant as the confidence intervals are wide and overlap.

Sensitivity, Specificity, False positive rates etc for active TB (as surrogates of patient relevant outcomes)

7,392 (3) No pooled results.

IGRA sensitivity for incident TB was 88% (64-99), 75% (48-93) and 75% (61-86) for the China (T-Spot.TB), Zambia (QFT-GIT) and South Africa (QFT-GIT) studies, respectively. Specificity was low across the studies at 35% (30-41), 50% (46-54) and 49% (48-51). That means, the false positive rate (100-specificity) for the studies will be 65% (59-70), 50% (46-54) and 51% (49-52). Based on a positive IGRA alone, all these individuals would unnecessarily receive IPT.

TST sensitivity for incident TB was similar at 76% (50-93) and 73% (59-84) for the China and South Africa studies, respectively. Specificity for those studies was 35% (29-41) and 58% (57-58). The proportions that would unnecessarily receive IPT based on IPT alone would be 65% (59-71) and 42% (41-42) for the China and South Africa studies, respectively. By contrast sensitivity for subsequent TB disease was poorest for the Zambia study at 44% (20-70) with a specificity of 67% (64-71). The Zambia study acknowledged logistical issues at the clinical sites that possibly affected TST results.

IGRA have moderate sensitivity for subsequent TB in keeping with observed moderate rates. This is not different from the TST.

False positive rate is similar for both tests.

The proportions scored positive by IGRA and TST are similar for the China and South Africa studies. By contrast, the proportion IGRA+ is higher than TST+ for the Zambia study. However, lower TST results may have resulted from logistical issues.

Very low

Important

(4-6)

Utility of repeated or serial IGRA results for predicting subsequent incident active TB

No studies Important

(4-6)

Operational aspects of the use of IGRAs in high TB burden countries

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3.7 Operational aspects on the use of IGRAs in high TB burden countries

Only a few studies addressed these aspects, mainly in the discussion and not systematically:

Cost

Cost of IGRAs was mentioned by four studies, mainly stating that the assays are too expensive and

therefore a limitation to their use.

Reproducibility

Only one study addressed reproducibility of T-SPOT by assessing inter-observer agreement, showing

excellent correlation. No other study mentioned the issue of test reproducibility.

Transport time

Twelve studies reported on accepted transport times of samples to the lab, which were mainly <6 hrs,

within the limit accepted by the test manufacturers. One study accepted 16 hrs and another 24 hrs

transport times. None reported on the impact of the transport times (ie. delay between drawing the

blood and initiating the IGRA test) and IGRA test results/performance.

Time to result

No study reported on time to result for IGRAs.

Impact of the use of IGRAs on treatment

Four studies reported on the impact of IGRAs on TB therapy. In two studies, IGRA results were reported

to clinicians; one study did not discuss the consequences and in the other QFT- positive children

received preventive chemotherapy. The other two studies commented on the reduced number of

patients that would require preventive therapy if IGRAs were part of the diagnostic algorithm.

Feasibility

The following aspects related to the feasibility of IGRAs were highlighted:

Phlebotomy can be difficult, particularly in very young children;

Blood amounts required may be an issue, however tests were performed with <2 ml of blood (T-

SPOT) in some studies;

Indeterminate results as well as failures due to low cell counts (T-SPOT) may be more frequent in

younger children (<4yrs) and immune-suppressed children;

Strong interferon response in negative control tubes (high background results) in QFT may reflect

the influence of other coincident diseases;

Standardization and generation of automated, quantitative results should render IGRAs more

objective than TST;

A well-equipped laboratory, expensive equipment and training are required for IGRA test

performance, which may cause logistical problems.

Annexes

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119

Annex 1. Meeting participants

Expert Group

Dr Richard A Adegbola Senior Program Officer Infectious Diseases, Global Health Bill & Melinda Gates Foundation P O Box 23350 Seattle, WA 98102 USA [email protected] Dr Lakhbir Singh Chauhan Deputy Director General of Health Services Ministry of Health and Family Welfare 522 "C" Wing, 5th Floor Nirman Bhavan 110011 - New Delhi India [email protected] Dr Daniela Cirillo Head, Emerging Bacterial Pathogens Unit San Raffaele del Monte Tabor Foundation (HSR), Emerging bacterial pathogens Via Olgettina 60 20132- Milan Italy [email protected] Dr Anneke C Hesseling Professor and Director: Paediatric TB Research Program, Desmond Tutu TB Centre Department of Paediatrics and Child Health, Faculty of Health Sciences Stellenbosch University Private Bag X1 Matieland, 7602 South Africa [email protected]

Dr Phillip Hill McAuley Professor of International Health Director, Centre for International Health Department of preventive and Social Medicine Univeristy of Otago School of Medicine PO BOX 913, Dunedin 9054 New Zealand [email protected] Mr Oluwamayowa Joel Communication for Development Centre 73, Ikosi Road, Ketu, Lagos State Nigeria [email protected] Dr Suman Laal Associate Professor of Pathology & Microbiology NYU Langone Medical Center c/o VA Medical Center 423 East 23rd Street, Room 18123N New York, NY 10010 USA [email protected] Dr Philip LoBue Associate Director for Science Division of Tuberculosis Elimination National Center for STD, HIV/AIDS, Viral Hepatitis, and TB Prevention Centers for Disease Control and Prevention 1600 Clifton Road Mailstop E-04 Atlanta , GA 30333 USA [email protected] Dr Holger Schünemann Department of Clinical Epidemiology & Biostatistics McMaster University Health Sciences Centre Room 2C10B, 1200 Main Street, West Hamilton Canada [email protected]








120

Systematic reviewers and observers Dr Adithya Cattamanchi San Francisco General Hospital Pulmonary Division – Room 5K1 1001 Potrero Ave San Francisco, CA 94110 USA [email protected] Dr Anand Date HIV/AIDS Care & Treatment Branch (HIV/TB) Global AIDS Program Centers for Disease Control & Prevention 1600 Clifton Road Mailstop E-04 Atlanta , GA 30333 USA [email protected] Dr Anne Detjen Technical Consultant The Union North America Office International Union Against Tuberculosis and Lung Disease 61 Broadway, Suite 1720 New York, NY 10006 USA [email protected] Dr Richard Menzies Montreal Chest Institute 3650 St. Urbain St. Montreal, PQ Canada H2X 2P4 [email protected] Dr John Metcalfe Division of Pulmonary and Critical Care Medicine University of California, San Francisco Division of Epidemiology University of California, Berkeley 230 Santa Paula Ave. San Francisco, CA 94127 USA [email protected]

Dr Richard J O'Brien Foundation for New Innovative New Diagnostics 16 Avenue de Budé 1202 Geneva Switzerland [email protected] Dr Madhukar Pai McGill University Dept of Epidemiology & Biostatistics 1020 Pine Ave West Montreal, QC H3A 1A2 Canada [email protected] Dr Molebogeng Rangaka Institute of Infectious Diseases and Molecular Medicine School of Health Sciences University of Cape Town Observatory, 7925 South Africa [email protected] [email protected] Dr Karen R Steingart Physician Consultant Curry International Tuberculosis Center University of California, San Francisco 3180 18th Street, Suite 101 San Francisco, CA 94110-2028 USA [email protected] Dr Alice Zwerling Montreal Chest Institute, Rm K3.09 3650 St Urbain, Montreal, Quebec H2X 2P4 Canada [email protected] Dr Peter Godfrey-Faussett Department of Infection & Tropical Diseases London School of Hygiene & Tropical Medicine Keppel Street WC1E 7HT - London United Kingdom [email protected]













121

WHO HQ Staff Dr Chris Gilpin, TBL [email protected] Mr Jean Iragena, TBL [email protected] Dr Christian Lienhardt, TBP [email protected] Dr Fuad Mirzayev, TBL [email protected] Dr Mario Raviglione, Director, STB [email protected] Dr Diana Weil, Coordinator, STB [email protected] Dr Karin Weyer, Coordinator, TBL [email protected] Dr Matteo Zignol, TBS [email protected] WHO/TDR Dr Luis Cuevas [email protected] Dr Andy Ramsay [email protected] WHO/TDR Dr Luis Cuevas [email protected] Dr Andy Ramsay [email protected]













122

Annex 2. Declarations of Interest

None declared

R. Adegbola

A. Cattamanchi

L. Chauhan

D. Cirillo

A. Hesseling

P. Hill

P. LoBue

H. Schüneman

J. Oluwamayowa

S. Laal

Declared, insignificant

R. O’Brien (FIND support to academia to develop POC serodiagnostic test, FIND

biomakarker discovery project)

Declared, significant (observer status)

D. Dowdy (relevant research, participation in systematic review)

M. Pai (relevant research, participation in systematic reviews)

J. Metcalf (principal systematic reviewer)

K. Steingart (principal systematic reviewer)

P. Godfrey-Fausset (relevant research)

A. Zwerling (principal systematic reviewer)

123

Annex 3. Selection of studies evaluating the use of IGRA in the diagnosis of active TB

Titles/abstracts identified and screened for full-text retrieval: 789

Excluded based on title and abstract: 621

Full papers retrieved for more detailed

evaluation: 168 Excluded: 134 Reasons Children: 1 Duplicate data: 2 Extrapulmonary TB: 2 Less than 10 TB patients: 3 LTBI: 93 Noncommercial IGRA: 8 Nonstandard IGRA method: 3 Older generation IGRA: 22

Pulmonary TB, all countries: 51

Added from prior systematic review: 17

High income countries: 32

Pulmonary TB, Low/middle income

countries

Papers 22 (studies 33)

Unpublished

investigations: 3

124

Included studies

1. Dheda K, van Zyl Smit R, Badri M and Pai M. T-cell interferon-gamma release assays for the rapid immunodiagnosis of tuberculosis: clinical utility in high-burden vs. low-burden settings. Curr Opin Pulm Med 2009;15:188-200

2. Jiang W, Shao L, Zhang Y, et al. High-sensitive and rapid detection of Mycobacterium tuberculosis infection by IFN-gamma release assay among HIV-infected individuals in BCG-vaccinated area. BMC Immunol 2009;10:31

3. Soysal A, Torun T, Efe S, Gencer H, Tahaoglu K and Bakir M. Evaluation of cut-off values of interferon-gamma-based assays in the diagnosis of M. tuberculosis infection. Int J Tuberc Lung Dis 2008;12:50-6

4. Aabye MG, Ravn P, PrayGod G, et al. The impact of HIV infection and CD4 cell count on the performance of an interferon gamma release assay in patients with pulmonary tuberculosis. PLoS One 2009;4:e4220

5. Cattamanchi A, Ssewenyana I, Davis JL, et al. Role of interferon-gamma release assays in the diagnosis of pulmonary tuberculosis in patients with advanced HIV infection. 2009

6. Chegou NN, Black GF, Kidd M, van Helden PD and Walzl G. Host markers in QuantiFERON supernatants differentiate active TB from latent TB infection: preliminary report. BMC Pulm Med 2009;9:21

7. Chen X, Yang Q, Zhang M, et al. Diagnosis of active tuberculosis in China using an in-house gamma interferon enzyme-linked immunospot assay. Clin Vaccine Immunol 2009;16:879-84

8. Dheda K, van Zyl-Smit RN, Meldau R, et al. Quantitative lung T cell responses aid the rapid diagnosis of pulmonary tuberculosis. Thorax 2009

9. Kabeer BSA, Sikhamani R, Swaminathan S, Perumal V, Paramasivam P and Raja A. Role of interferon gamma release assay in active TB diagnosis among HIV infected individuals. PLoS One 2009;4:e5718

10. Katiyar SK, Sampath A, Bihari S, Mamtani M and Kulkarni H. Use of the QuantiFERON-TB Gold In-Tube test to monitor treatment efficacy in active pulmonary tuberculosis. Int J Tuberc Lung Dis 2008;12:1146-52

11. Leidl L, Mayanja-Kizza H, Sotgiu G, et al. Relationship of immunodiagnostic assays for tuberculosis and numbers of circulating CD4+ T-cells in HIV-infection. Eur Respir J 2009

12. Markova R, Todorova Y, Drenska R, Elenkov I, Yankova M and Stefanova D. Usefulness of interferon-gamma release assays in the diagnosis of tuberculosis infection in HIV-infected patients in Bulgaria. Biotechnol. & Biotechnol 2009;23:1103-8

13. Oni T, Patel J, Gideon HP, et al. Enhanced diagnosis of HIV-1 associated tuberculosis by relating T-SPOT.TB and CD4 counts. Eur Respir J 2010

14. Ozekinci T, Ozbek E and Celik Y. Comparison of tuberculin skin test and a specific T-cell-based test, T-Spot.TB, for the diagnosis of latent tuberculosis infection. J Int Med Res 2007;35:696-703

15. Pai M, Joshi R, Bandyopadhyay M, et al. Sensitivity of a whole-blood interferon-gamma assay among patients with pulmonary tuberculosis and variations in T-cell responses during anti-tuberculosis treatment. Infection 2007;35:98-103

16. Raby E, Moyo M, Devendra A, et al. The effects of HIV on the sensitivity of a whole blood IFN-gamma release assay in Zambian adults with active tuberculosis. PLoS One 2008;3:e2489

125

17. Shao-ping. Enzyme-linked immunospot assay combined with serum latex agglutination test for diagnosis of pulmonary tuberculosis and concomitant pulmonary cryptococcosis. Chin J Infect Chemo 2009

18. Tahereh K, Alireza N, Massoud S and Amina K. A validity study of the QuantiFERON-TB Gold (QFT-TB) method for the diagnosis of pulmonary tuberculosis in a high risk population. Swiss Medical Weekly 2010;140:95-96

19. Tsiouris SJ, Coetzee D, Toro PL, Austin J, Stein Z and El-Sadr W. Sensitivity analysis and potential uses of a novel gamma interferon release assay for diagnosis of tuberculosis. J Clin Microbiol 2006;44:2844-50

20. Veldsman C, Kock MM, Rossouw T, et al. QuantiFERON-TB GOLD ELISA assay for the detection of Mycobacterium tuberculosis-specific antigens in blood specimens of HIV-positive patients in a high-burden country. FEMS Immunol Med Microbiol 2009

21. M X Rangaka, H Gideon, K A Wilkinson, et al. The incremental value of IGRA for pulmonary TB in HIV-infected patients in an ART program (unpublished).

22. Ling D, Pai M, Davids V, et al. Incremental Value Of Interferon-Gamma Release Assays For Diagnosis Of Active Tuberculosis In Smear-Negative Patients In A High-Burden Setting: A Multivariable Analysis. Abstract: Am. J. Respir. Crit. Care Med. May 2010;181:A2262

Excluded studies (Reasons for exclusion in parenthesis after reference)

1. Targeted tuberculin testing and treatment of latent tuberculosis infection. This official statement of the American Thoracic Society was adopted by the ATS Board of Directors, July 1999. This is a Joint Statement of the American Thoracic Society (ATS) and the Centers for Disease Control and Prevention (CDC). This statement was endorsed by the Council of the Infectious Diseases Society of America. (IDSA), September 1999, and the sections of this statement. Am J Respir Crit Care Med. 2000 Apr;161(4 Pt 2):S221-47. (LTBI)

2. BTS recommendations for assessing risk and for managing Mycobacterium tuberculosis infection and disease in patients due to start anti-TNF-alpha treatment. Thorax. 2005 Oct;60(10):800-5. (LTBI)

3. Centers for Disease Control and Prevention. Updated Guidelines for Using Interferon Gamma Release Assays to Detect Mycobacterium tuberculosis Infection - United States, 2010. MMWR. 2010;59(RR-5). (LTBI)

4. Canadian Tuberculosis Committee. Updated Recommendations on Interferon Gamma Release Assays for Latent Tuberculosis Infection. CCDR. 2010;36(ACS-5):1-21. (LTBI)

5. Adetifa IM, Lugos MD, Hammond A, Jeffries D, Donkor S, Adegbola RA, et al. Comparison of Two Interferon Gamma Release Assays in the diagnosis of Mycobacterium tuberculosis infection and disease in The Gambia. BMC Infect Dis. 2007 Oct 25;7(1):122. (Nonstandard IGRA method)

6. Aichelburg MC, Rieger A, Breitenecker F, Pfistershammer K, Tittes J, Eltz S, et al. Detection and prediction of active tuberculosis disease by a whole-blood interferon-gamma release assay in HIV-1-infected individuals. Clin Infect Dis. 2009 Apr 1;48(7):954-62. (Fewer than 10 TB cases)

7. Ak O, Dabak G, Ozer S, Saygi A, Dabak R. The evaluation of the Quantiferon-TB Gold test in pulmonary and extrapulmonary tuberculosis. Jpn J Infect Dis. 2009 Mar;62(2):149-51. (Older generation IGRA)

126

8. Baba K, Sornes S, Hoosen AA, Lekabe JM, Mpe MJ, Langeland N, et al. Evaluation of immune responses in HIV infected patients with pleural tuberculosis by the QuantiFERON TB-Gold interferon-gamma assay. BMC Infect Dis. 2008;8:35. (Extrapulmonary TB)

9. Bakir M, Millington KA, Soysal A, Deeks JJ, Efee S, Aslan Y, et al. Prognostic value of a T-cell-based, interferon-gamma biomarker in children with tuberculosis contact. Ann Intern Med. 2008 Dec 2;149(11):777-87. (LTBI)

10. Balcells ME, Perez CM, Chanqueo L, Lasso M, Villanueva M, Espinoza M, et al. A comparative study of two different methods for the detection of latent tuberculosis in HIV-positive individuals in Chile. Int J Infect Dis. 2008 Nov;12(6):645-52. (LTBI)

11. Barry CE, 3rd, Boshoff HI, Dartois V, Dick T, Ehrt S, Flynn J, et al. The spectrum of latent tuberculosis: rethinking the biology and intervention strategies. Nat Rev Microbiol. 2009 Oct 26. (LTBI)

12. Bartalesi F, Vicidomini S, Goletti D, Fiorelli C, Fiori G, Melchiorre D, et al. QuantiFERON-TB Gold and the TST are both useful for latent tuberculosis infection screening in autoimmune diseases. Eur Respir J. 2009 Mar;33(3):586-93. (LTBI)

13. Beglinger C, Dudler J, Mottet C, Nicod L, Seibold F, Villiger PM, et al. Screening for tuberculosis infection before the initiation of an anti-TNF-alpha therapy. Swiss Med Wkly. 2007 Nov 3;137(43-44):620-2. (LTBI)

14. Behar SM, Shin DS, Maier A, Coblyn J, Helfgott S, Weinblatt ME. Use of the T-SPOT.TB assay to detect latent tuberculosis infection among rheumatic disease patients on immunosuppressive therapy. J Rheumatol. 2009 Mar;36(3):546-51. (LTBI)

15. Bienek DR, Chang CK. Evaluation of an interferon-gamma release assay, T-SPOT.TB, in a population with a low prevalence of tuberculosis. Int J Tuberc Lung Dis. 2009 Nov;13(11):1416-21. (LTBI)

16. Bocchino M, Matarese A, Bellofiore B, Giacomelli P, Santoro G, Balato N, et al. Performance of two commercial blood IFN-gamma release assays for the detection of Mycobacterium tuberculosis infection in patient candidates for anti-TNF-alpha treatment. Eur J Clin Microbiol Infect Dis. 2008 Oct;27(10):907-13. (LTBI)

17. Bongartz T, Sutton AJ, Sweeting MJ, Buchan I, Matteson EL, Montori V. Anti-TNF antibody therapy in rheumatoid arthritis and the risk of serious infections and malignancies: systematic review and meta-analysis of rare harmful effects in randomized controlled trials. JAMA. 2006 May 17;295(19):2275-85. (LTBI)

18. Brassard P, Kezouh A, Suissa S. Antirheumatic drugs and the risk of tuberculosis. Clin Infect Dis. 2006 Sep 15;43(6):717-22. (LTBI)

19. Brock I, Ruhwald M, Lundgren B, Westh H, Mathiesen LR, Ravn P. Latent tuberculosis in HIV positive, diagnosed by the M. tuberculosis specific interferon-gamma test. Respir Res. 2006;7:56. (LTBI)

20. Brock I, Weldingh K, Lillebaek T, Follmann F, Andersen P. Comparison of tuberculin skin test and new specific blood test in tuberculosis contacts. Am J Respir Crit Care Med. 2004 Jul 1;170(1):65-9. (Older generation IGRA)

21. Bua A, Molicotti P, Delogu G, Pirina P, Mura MS, Madeddu G, et al. QuantiFERON TB Gold: a new method for latent tuberculosis infection. New Microbiol. 2007 Oct;30(4):477-80. (Older generation IGRA)

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131. Winthrop KL. Risk and prevention of tuberculosis and other serious opportunistic infections associated with the inhibition of tumor necrosis factor. Nat Clin Pract Rheumatol. 2006 Nov;2(11):602-10. (LTBI)

132. Winthrop KL. Serious infections with antirheumatic therapy: are biologicals worse? Ann Rheum Dis. 2006 Nov;65 Suppl 3:iii54-7. (LTBI)

133. Winthrop KL. The Risk and Prevention of Tuberculosis: Screening Strategies to Detect Latent Tuberculosis Among Rheumatoid Arthritis Patients Who Use Biologic Therapy. Int J Adv Rheumatol. 2010;8(2):43-52. (LTBI)

134. Winthrop KL, Chiller T. Preventing and treating biologic-associated opportunistic infections. Nat Rev Rheumatol. 2009 Jul;5(7):405-10. (LTBI)

135

Annex 4. Selection of studies evaluating the use of IGRAs in children

Included studies 1. Adetifa IM, Ota MO, Jeffries DJ, et al. Commercial interferon gamma release assays

compared to the tuberculin skin test for diagnosis of latent Mycobacterium tuberculosis infection in childhood contacts in the Gambia. Pediatr Infect Dis J 2010;29:439-43.

2. Bamford AR, Crook AM, Clark J, et al. Comparison of Interferon-gamma release assays and Tuberculin Skin Test in predicting active tuberculosis (TB) in children in the UK- a Paediatric TB Network Study. Arch Dis Child 2009.

136

3. Bergamini BM, Losi M, Vaienti F, et al. Performance of Commercial Blood Tests for the Diagnosis of Latent Tuberculosis Infection in Children and Adolescents. Pediatrics 2009;123:e419-e24.

4. Bianchi L, Galli L, Moriondo M, et al. Interferon-Gamma Release Assay Improves the Diagnosis of Tuberculosis in Children. Pediatric Infectious Disease Journal 2009;28:510-4.

5. Chun JK, Kim CK, Kim HS, et al. The role of a whole blood interferon-gamma assay for the detection of latent tuberculosis infection in Bacille Calmette-Guerin vaccinated children. Diagn Microbiol Infect Dis 2008;62:389-94.

6. Connell TG, Curtis N, Ranganathan SC, Buttery JP. Performance of a whole blood interferon gamma assay for detecting latent infection with Mycobacterium tuberculosis in children. Thorax 2006;61:616-20.

7. Connell TG, Ritz N, Paxton GA, Buttery JP, Curtis N, Ranganathan SC. A three-way comparison of tuberculin skin testing, QuantiFERON-TB gold and T-SPOT.TB in children. PLoS One 2008;3:e2624.

8. Detjen AK, Keil T, Roll S, et al. Interferon-gamma release assays improve the diagnosis of tuberculosis and nontuberculous mycobacterial disease in children in a country with a low incidence of tuberculosis. Clinical Infectious Diseases 2007;45:322-8.

9. Diel R, Loddenkemper R, Meywald-Walter K, Niemann S, Nienhaus A. Predictive value of a whole blood IFN-gamma assay for the development of active tuberculosis disease after recent infection with Mycobacterium tuberculosis. Am J Respir Crit Care Med 2008;177:1164-70.

10. Dogra S, Naraing P, Mendiratta DK, et al. Comparison of a whole blood interferon-gamma assay with tuberculin skin testing for the detection of tuberculosis infection in hospitalized children in rural India. Journal of Infection 2007;54:267-76.

11. Dominguez J, Ruiz-Manzano J, De Souza-Galvao M, et al. Comparison of two commercially available gamma interferon blood tests for immunodiagnosis of tuberculosis. Clinical and Vaccine Immunology 2008;15:168-71.

12. Girardi E, Loffredo M, Alessandrini A, Anzidei G, Goletti D. A two-step approach for screening contacts of active tuberculosis. Infection 2007;35:122-3.

13. Grare M, Derelle J, Dailloux M, Laurain C. QuantiFERON((R))-TB Gold In-Tube as help for the diagnosis of tuberculosis in a French pediatric hospital. Diagn Microbiol Infect Dis 2010.

14. Hansted E, Andriuskeviciene A, Sakalauskas R, Kevalas R, Sitkauskiene B. T-cell-based diagnosis of tuberculosis infection in children in Lithuania: a country of high incidence despite a high coverage with bacille Calmette-Guerin vaccination. BMC Pulm Med 2009;9:41.

15. Haustein T, Ridout DA, Hartley JC, et al. The Likelihood of an Indeterminate Test Result from a Whole-Blood Interferon-gamma Release Assay for the Diagnosis of Mycobacterium tuberculosis Infection in Children Correlates With Age and Immune Status. Pediatric Infectious Disease Journal 2009;28:669-73.

16. Herrmann JL, Belloy M, Porcher R, et al. Temporal dynamics of interferon gamma responses in children evaluated for tuberculosis. PLoS One 2009;4:e4130.

17. Hesseling AC, Mandalakas AM, Kirchner HL, et al. Highly discordant T cell responses in individuals with recent exposure to household tuberculosis. Thorax 2009;64:840-6.

18. Higuchi K, Harada N, Fukazawa K, Mori T. Relationship between whole-blood interferon-gamma responses and the risk of active tuberculosis. Tuberculosis (Edinb) 2008;88:244-8.

137

19. Higuchi K, Kondo S, Wada M, et al. Contact investigation in a primary school using a whole blood interferon-gamma assay. Journal of Infection 2009;58:352-7.

20. Higuchi R, Mori M, Ozawa R, et al. Whole blood interferon-gamma assay for tuberculosis in children in Japan. Pediatrics International 2009;51:97-102.

21. Kampmann B, Whittaker E, Williams A, et al. Interferon-gamma release assays do not identify more children with active tuberculosis than the tuberculin skin test. European Respiratory Journal 2009;33:1374-82.

22. Lighter J, Rigaud M, Eduardo R, Peng CH, Pollack H. Latent Tuberculosis Diagnosis in Children by Using the QuantiFERON-TB Gold In-Tube Test. Pediatrics 2009;123:30-7.

23. Lucas M, Nicol P, McKinnon E, et al. A prospective large-scale study of methods for the detection of latent Mycobacterium tuberculosis infection in refugee children. Thorax 2010;65:442-8.

24. Mandalakas AM, Hesseling AC, Chegou NN, et al. High level of discordant IGRA results in HIV-infected adults and children. International Journal of Tuberculosis and Lung Disease 2008;12:417-23.

25. Moyo S, Isaacs F, Gelderbloem S, et al. TST and Interferon-gamma release assay in young child TB suspects in a high incidence setting. Pediatrics submitted.

26. Nakaoka H, Lawson L, Squire SB, et al. Risk for tuberculosis among children. Emerging Infectious Diseases 2006;12:1383-8.

27. Nicol MP, Davies MA, Wood K, et al. Comparison of T-SPOT.TB assay and tuberculin skin test for the evaluation of young children at high risk for tuberculosis in a community setting. Pediatrics 2009;123:38-43.

28. Okada K, Mao TE, Mori T, et al. Performance of an interferon-gamma release assay for diagnosing latent tuberculosis infection in children. Epidemiology and Infection 2008;136:1179-87.

29. Petrucci R, Amer NA, Gurgel RQ, et al. Interferon Gamma, Interferon-Gamma-induced-Protein 10, and Tuberculin Responses of Children at High Risk of Tuberculosis Infection. Pediatric Infectious Disease Journal 2008;27:1073-7.

30. Stavri H, Ene L, Popa GL, et al. Comparison of tuberculin skin test with a whole-blood interferon gamma assay and ELISA, in HIV positive children and adolescents with TB. Roum Arch Microbiol Immunol 2009;68:14-9.

31. Stefan DC, Dippenaar A, Detjen AK, et al. Interferon-gamma release assays for the detection of Mycobacterium tuberculosis infection in children with cancer. Int J Tuberc Lung Dis 2010;14:689-94.

32. Warier A, Gunawathi S, Venkatesh S, John KR, Bose A. T-Cell Assay as a Diagnostic Tool for Tuberculosis. Indian Pediatr 2009.

Studies excluded after full text review (Reasons for exclusion in parenthesis after reference)

1. Adetifa IMO, Lugos MD, Hammond A, et al. Comparison of two interferon gamma release assays in the diagnosis of Mycobacterium tuberculosis infection and disease in The Gambia. Bmc Infectious Diseases 2007;7. (Data not available)

2. Arend SM, Thijsen SF, Leyten EM, et al. Comparison of two interferon-gamma assays and tuberculin skin test for tracing tuberculosis contacts. Am J Respir Crit Care Med 2007;175:618-27. (<20 children)

3. Bakir M, Millington KA, Soysal A, et al. Prognostic Value of a T-Cell-Based, Interferon-gamma Biomarker in Children with Tuberculosis Contact. Annals of Internal Medicine 2008;149:777-W163. (Pre-commercial ELISPOT)

138

4. Beffa P, Zellweger A, Janssens JP, Wrighton-Smith P, Zellweger JP. Indeterminate test results of T-SPOT (TM).TB performed under routine field conditions. European Respiratory Journal 2008;31:842-6. (No exposure gradient)

5. Bruzzese E, Bocchino M, Assante LR, et al. Gamma interferon release assays for diagnosis of tuberculosis infection in immune-compromised children in a country in which the prevalence of tuberculosis is low. J Clin Microbiol 2009;47:2355-7. (No exposure gradient)

6. Connell TG, Davies MA, Johannisen C, et al. Reversion and conversion of Mycobacterium tuberculosis IFN-gamma ELISpot results during anti-tuberculous treatment in HIV-infected children. BMC Infect Dis 2010;10:138. (Overlap with included publications)

7. Connell TG, Tebruegge M, Ritz N, Bryant PA, Leslie D, Curtis N. Indeterminate interferon-gamma release assay results in children. Pediatr Infect Dis J 2010;29:285-6. (Pre-commercial ELISPOT)

8. Davies MA, Connell T, Johannisen C, et al. Detection of tuberculosis in HIV-infected children using an enzyme-linked immunospot assay. Aids 2009;23:961-9. (Pre-commercial ELISPOT)

9. Dewan PK, Grinsdale J, Kawamura LM. Low sensitivity of a whole-blood interferon-gamma release assay for detection of active tuberculosis. Clin Infect Dis 2007;44:69-73. (Data not available)

10. Eisenhut M, Paranjothy S, Abubakar I, et al. BCG vaccination reduces risk of infection with Mycobacterium tuberculosis as detected by gamma interferon release assay. Vaccine 2009;27:6116-20. (IGRA testing only in TST positive – no comparison possible)

11. Ferrara G, Losi M, D'Amico R, et al. Use in routine clinical practice of two commercial blood tests for diagnosis of infection with Mycobacterium tuberculosis: a prospective study. Lancet 2006;367:1328-34. (Data not available)

12. Ferrara G, Losi M, Meacci M, et al. Routine hospital use of a new commercial whole blood interferon-gamma assay for the diagnosis of tuberculosis infection. Am J Respir Crit Care Med 2005;172:631-5. (Data not available)

13. Higuchi K, Harada N, Mori T, Sekiya Y. Use of QuantiFERON-TB Gold to investigate tuberculosis contacts in a high school. Respirology 2007;12:88-92. (QFT-G testing only in TST positive – no comparison possible)

14. Kang YA, Lee HW, Hwang SS, et al. Usefulness of whole-blood interferon-gamma assay and interferon-gamma enzyme-linked immunospot assay in the diagnosis of active pulmonary tuberculosis. Chest 2007;132:959-65. (No children included)

15. Kobashi Y, Mouri K, Miyashita N, et al. QuantiFERON TB-2G test for patients with active tuberculosis stratified by age groups. Scandinavian Journal of Infectious Diseases 2009;41:841-6. (Pediatric data not available)

16. Kobashi Y, Mouri K, Obase Y, Fukuda M, Miyashita N, Oka M. Clinical evaluation of QuantiFERON TB-2G test for immunocompromised patients. European Respiratory Journal 2007;30:945-50. (Pediatric data not available)

17. Latorre I, De Souza-Galvao M, Ruiz-Manzano J, et al. Quantitative evaluation of T-cell response after specific antigen stimulation in active and latent tuberculosis infection in adults and children. Diagn Microbiol Infect Dis 2009;65:236-46. (Incorporation bias for TST and IGRAs)

18. Lee JY, Choi HJ, Park IN, et al. Comparison of two commercial interferon-gamma assays for diagnosing Mycobacterium tuberculosis infection. Eur Respir J 2006;28:24-30. (Pediatric data not available)

139

19. Lew WJ, Jung YJ, Song JW, et al. Combined use of QuantiFERON (R)-TB Gold assay and chest computed tomography in a tuberculosis outbreak. International Journal of Tuberculosis and Lung Disease 2009;13:633-9. (<20 children)

20. Liebeschuetz S, Bamber S, Ewer K, Deeks J, Pathan AA, Lalvani A. Diagnosis of tuberculosis in South African children with a T-cell-based assay: a prospective cohort study. Lancet 2004;364:2196-203. (Pre-commercial IGRA)

21. Mantegani P, Piana F, Codecasa L, et al. Comparison of an in-house and a commercial RD1-based ELISPOT-IFN-gamma assay for the diagnosis of Mycobacterium tuberculosis infection. Clin Med Res 2006;4:266-72. (<20 children)

22. Molicotti P, Bua A, Mela G, et al. Performance of QuantiFERON-TB testing in a tuberculosis outbreak at a primary school. Journal of Pediatrics 2008;152:585-6. (No exposure gradient)

23. Neira-Munoz E, Smith J, Cockcroft P, Basher D, Abubaker I. Extensive transmission of Mycobacterium tuberculosis among children on a school bus. Pediatric Infectious Disease Journal 2008;27:836-7. (No exposure gradient)

24. Nicol MP, Pienaar D, Wood K, et al. Enzyme-linked immunospot assay responses to early secretory antigenic target 6, culture filtrate protein 10, and purified protein derivative among children with tuberculosis: Implications for diagnosis and monitoring of therapy. Clinical Infectious Diseases 2005;40:1301-8. (Pre-commercial IGRA)

25. Nienhaus A, Schablon A, Diel R. Interferon-gamma release assay for the diagnosis of latent TB infection--analysis of discordant results, when compared to the tuberculin skin test. PLoS One 2008;3:e2665. (<20 children)

26. Nsutebu E, Moffitt SJ, Mullarkey C, Schweiger MS, Collyns T, Watson JP. Use of QuantiFERON-TB Gold test in the investigation of unexplained positive tuberculin skin tests. Public Health 2008;122:1284-7. (Stepwise testing and no exposure groups)

27. Ozekinci T, Ozbek E, Celik Y. Comparison of tuberculin skin test and a specific T-cell-based test, T-Spot (TM).TB, for the diagnosis of latent tuberculosis infection. Journal of International Medical Research 2007;35:696-703. (Data not available)

28. Pai M, Joshi R, Dogra S, et al. T-cell assay conversions and reversions among household contacts of tuberculosis patients in rural India. Int J Tuberc Lung Dis 2009;13:84-92. (Data not available)

29. Piana F, Ruffo Codecasa L, Baldan R, Miotto P, Ferrarese M, Cirillo DM. Use of T-SPOT.TB in latent tuberculosis infection diagnosis in general and immunosuppressed populations. New Microbiol 2007;30:286-90. (Data not available)

30. Ruhwald M, Petersen J, Kofoed K, et al. Improving T-cell assays for the diagnosis of latent TB infection: potential of a diagnostic test based on IP-10. PLoS One 2008;3:e2858. (Overlap with included publication)

31. Soysal A, Millington KA, Bakir M, et al. Effect of BCG vaccination on risk of Mycobacterium tuberculosis infection in children with household tuberculosis contact: a prospective community-based study. Lancet 2005;366:1443-51. (Pre-commercial IGRA)

32. Soysal A, Turel O, Toprak D, Bakir M. Comparison of positive tuberculin skin test with an interferon-gamma-based assay in unexposed children. Jpn J Infect Dis 2008;61:192-5. (No exposure gradient and stepwise testing plus one IGRA only – no comparison possible)

33. Taylor REB, Cant AJ, Clark JE. Potential effect of NICE tuberculosis guidelines on paediatric tuberculosis screening. Archives of Disease in Childhood 2008;93:200-3. (No exposure gradient)

140

34. Tsiouris SJ, Austin J, Toro P, et al. Results of a tuberculosis-specific IFN-gamma assay in children at high risk for tuberculosis infection. International Journal of Tuberculosis and Lung Disease 2006;10:939-41. (No exposure gradient)

35. Wang JY, Chou CH, Lee LN, et al. Diagnosis of tuberculosis by an enzyme-linked immunospot assay for interferon-gamma. Emerg Infect Dis 2007;13:553-8. (Data not available)

36. Winje BA, Oftung F, Korsvold GE, et al. School based screening for tuberculosis infection in Norway: comparison of positive tuberculin skin test with interferon-gamma release assay. Bmc Infectious Diseases 2008;8. (Stepwise testing plus one IGRA only – no comparison possible)

141

Annex 5. Selection of studies evaluating the use of IGRAs for the diagnosis of LTBI in HIV-positive individuals

Included studies 1. Aichelburg MC, Rieger A, Breitenecker F, et al. Detection and prediction of active

tuberculosis disease by a whole-blood interferon-gamma release assay in HIV-1-infected individuals. Clin Infect Dis. Apr 1 2009;48(7):954-962.

2. Clark SA, Martin SL, Pozniak A, et al. Tuberculosis antigen-specific immune responses can be detected using enzyme-linked immunospot technology in human

Titles/abstracts identified and screened for

full-text retrieval: 791

Excluded based on title and abstract: 662

Full papers retrieved for more detailed evaluation:

129

Excluded: 100 Reasons: Case report or series 2 Data insufficient 2 Duplicate data 2 HIV status by self-report 1 Older generation IGRA 5 Noncommercial IGRA 9 <10 HIV-infected persons 77 Reference standard lacking 2

Papers (comparisons) included:

29 (36 comparisons)

142

immunodeficiency virus (HIV)-1 patients with advanced disease. Clin Exp Immunol. Nov 2007;150(2):238-244.

3. Aabye MG, Ravn P, PrayGod G, et al. The impact of HIV infection and CD4 cell count on the performance of an interferon gamma release assay in patients with pulmonary tuberculosis. PLoS One. 2009;4(1):e4220.

4. Baba K, Sornes S, Hoosen AA, et al. Evaluation of immune responses in HIV infected patients with pleural tuberculosis by the QuantiFERON TB-Gold interferon-gamma assay. BMC Infect Dis. 2008;8:35.

5. Cattamanchi A, Ssewenyana I, Davis JL, et al. Role of interferon-gamma release assays in the diagnosis of pulmonary tuberculosis in patients with advanced HIV infection. 2009.

6. Dheda K, van Zyl-Smit RN, Meldau R, et al. Quantitative lung T cell responses aid the rapid diagnosis of pulmonary tuberculosis. Thorax. Jul 9 2009.

7. Jiang W, Shao L, Zhang Y, et al. High-sensitive and rapid detection of Mycobacterium tuberculosis infection by IFN-gamma release assay among HIV-infected individuals in BCG-vaccinated area. BMC Immunol. 2009;10:31.

8. Kabeer BSA, Sikhamani R, Swaminathan S, Perumal V, Paramasivam P, Raja A. Role of interferon gamma release assay in active TB diagnosis among HIV infected individuals. PLoS One. 2009;4(5):e5718.

9. Leidl L, Mayanja-Kizza H, Sotgiu G, et al. Relationship of immunodiagnostic assays for tuberculosis and numbers of circulating CD4+ T-cells in HIV-infection. Eur Respir J. Jul 16 2009.

10. Markova R, Todorova Y, Drenska R, Elenkov I, Yankova M, Stefanova D. Usefulness of interferon-gamma release assays in the diagnosis of tuberculosis infection in HIV-infected patients in Bulgaria. Biotechnol. & Biotechnol. 2009;23(1):1103-1108.

11. Oni T, Patel J, Gideon HP, et al. Enhanced diagnosis of HIV-1 associated tuberculosis by relating T-SPOT.TB and CD4 counts. Eur Respir J. Jan 14 2010 [Epub ahead of print].

12. Veldsman C, Kock MM, Rossouw T, et al. QuantiFERON-TB GOLD ELISA assay for the detection of Mycobacterium tuberculosis-specific antigens in blood specimens of HIV-positive patients in a high-burden country. FEMS Immunol Med Microbiol. Sep 11 2009.

13. Ling DI, Pai M, Davids V, et al. Incremental Value Of Interferon-Gamma Release Assays For Diagnosis Of Active Tuberculosis In Smear-Negative Patients In A High-Burden Setting: A Multivariable Analysis. Am. J. Respir. Crit. Care Med. 2010;181(MeetingAbstracts):A2262.

14. Sauzullo I, Mengoni F, Scrivo R, et al. Evaluation of QuantiFERON-TB Gold In-Tube in HIV infection and in patient candidates for anti-TNF-alpha therapy. Int J Tuberc Lung Dis. July 2010; 14(7):834-40.

15. Balcells ME, Perez CM, Chanqueo L, et al. A comparative study of two different methods for the detection of latent tuberculosis in HIV-positive individuals in Chile. Int J Infect Dis. Nov 2008; 12(6):645-652.

16. Hoffmann M, Reichmuth M, Fantelli K, et al. Conventional tuberculin skin testing versus T-cell-based assays in the diagnosis of latent tuberculosis infection in HIV-positive patients. AIDS. Jan 30 2007; 21(3):390-392.

17. Jones S, de Gijsel D, Wallach FR, Gurtman AC, Shi Q, Sacks H. Utility of QuantiFERON-TB Gold in-tube testing for latent TB infection in HIV-infected individuals. Int J Tuberc Lung Dis. Nov 2007;11(11):1190-1195.

18. Luetkemeyer AF, Charlebois ED, Flores LL, et al. Comparison of an interferon-gamma release assay with tuberculin skin testing in HIV-infected individuals. Am J Respir Crit Care Med. Apr 1 2007;175(7):737-742.

143

19. Mandalakas AM, Hesseling AC, Chegou NN, et al. High level of discordant IGRA results in HIV-infected adults and children. Int J Tuberc Lung Dis. Apr 2008;12(4):417-423.

20. Richeldi L, Losi M, D'Amico R, et al. Performance of tests for latent tuberculosis in different groups of immunocompromised patients. Chest. Jul 2009;136(1):198-204.

21. Rivas I, Latorre I, Sanvisens A, et al. Prospective evaluation of latent tuberculosis with interferon-gamma release assays in drug and alcohol abusers. Epidemiol Infect. Sep 2009;137(9):1342-1347.

22. Stephan C, Wolf T, Goetsch U, et al. Comparing QuantiFERON-tuberculosis gold, T-SPOT tuberculosis and tuberculin skin test in HIV-infected individuals from a low prevalence tuberculosis country. AIDS. Nov 30 2008;22(18):2471-2479.

23. Talati NJ, Seybold U, Humphrey B, et al. Poor concordance between interferon-gamma release assays and tuberculin skin tests in diagnosis of latent tuberculosis infection among HIV-infected individuals. BMC Infect Dis. 2009;9:15.

24. Dheda K, Lalvani A, Miller RF, et al. Performance of a T-cell-based diagnostic test for tuberculosis infection in HIV-infected individuals is independent of CD4 cell count. AIDS. Nov 18 2005;19(17):2038-2041.

25. Rangaka MX, Wilkinson KA, Seldon R, et al. Effect of HIV-1 infection on T-Cell-based and skin test detection of tuberculosis infection. Am J Respir Crit Care Med. Mar 1 2007;175(5):514-520.

26. Brock I, Ruhwald M, Lundgren B, Westh H, Mathiesen LR, Ravn P. Latent tuberculosis in HIV positive, diagnosed by the M. tuberculosis specific interferon-gamma test. Respir Res. 2006;7:56.

27. Garfein RS, Lozada R, Liu L, et al. High prevalence of latent tuberculosis infection among injection drug users in Tijuana, Mexico. Int J Tuberc Lung Dis. May 2009;13(5):626-632.

28. Elliott JH, Vohith K, Saramony S, et al. Immunopathogenesis and diagnosis of tuberculosis and tuberculosis-associated immune reconstitution inflammatory syndrome during early antiretroviral therapy. J Infect Dis. Dec 1 2009;200(11):1736-1745.

29. Dheda K, Smit RZ, Badri M, Pai M. T-cell interferon-gamma release assays for the rapid immunodiagnosis of tuberculosis: clinical utility in high-burden vs. low-burden settings. Curr Opin Pulm Med. May 2009;15(3):188-200.


1. Angus J, Roberts C, Kulkarni K, Leach I, Murphy R. Usefulness of the QuantiFERON test in the confirmation of latent tuberculosis in association with erythema induratum. Br J Dermatol. 2007 Dec;157(6):1293-4. (<10 HIV-infected individuals)

2. Arend SM, Leyten EM, Franken WP, Huisman EM, van Dissel JT. A patient with de novo tuberculosis during anti-tumor necrosis factor-alpha therapy illustrating diagnostic pitfalls and paradoxical response to treatment. Clin Infect Dis. 2007 Dec 1;45(11):1470-5. (<10 HIV-infected individuals)

3. Askling J, Fored CM, Brandt L, Baecklund E, Bertilsson L, Coster L, et al. Risk and case characteristics of tuberculosis in rheumatoid arthritis associated with tumor necrosis factor antagonists in Sweden. Arthritis Rheum. 2005 Jul;52(7):1986-92. (<10 HIV-infected individuals)

4. Bartalesi F, Vicidomini S, Goletti D, Fiorelli C, Fiori G, Melchiorre D, et al. QuantiFERON-TB Gold and the TST are both useful for latent tuberculosis infection screening in autoimmune diseases. Eur Respir J. 2009 Mar;33(3):586-93. (<10 HIV-infected individuals)

144

5. Behar SM, Shin DS, Maier A, Coblyn J, Helfgott S, Weinblatt ME. Use of the T-SPOT.TB assay to detect latent tuberculosis infection among rheumatic disease patients on immunosuppressive therapy. J Rheumatol. 2009 Mar;36(3):546-51. (<10 HIV-infected individuals)

6. Bellofiore B, Matarese A, Balato N, Gaudiello F, Scarpa R, Atteno M, et al. Prevention of Tuberculosis in Patients Taking Tumor Necrosis Factor-{alpha} Blockers. J Rheumatol Suppl. 2009 Aug;83:76-7. (<10 HIV-infected individuals)

7. Bergeron A, Herrmann JL. Screening for tuberculosis before TNFalpha antagonist initiation: are current methods good enough? Joint Bone Spine. 2008 Mar;75(2):112-5. (<10 HIV-infected individuals)

8. Bocchino M, Matarese A, Bellofiore B, Giacomelli P, Santoro G, Balato N, et al. Performance of two commercial blood IFN-gamma release assays for the detection of Mycobacterium tuberculosis infection in patient candidates for anti-TNF-alpha treatment. Eur J Clin Microbiol Infect Dis. 2008 Oct;27(10):907-13. (<10 HIV-infected individuals)

9. Brogden P, Varma A, Backhouse O. Interferon-gamma assay in tuberculous uveitis. Br J Ophthalmol. 2008 Apr;92(4):582-3. (<10 HIV-infected individuals)

10. Chapman AL, Munkanta M, Wilkinson KA, Pathan AA, Ewer K, Ayles H, et al. Rapid detection of active and latent tuberculosis infection in HIV-positive individuals by enumeration of Mycobacterium tuberculosis-specific T cells. AIDS. 2002 Nov 22;16(17):2285-93. (Noncommercial IGRA)

11. Chen DY, Shen GH, Hsieh TY, Hsieh CW, Lan JL. Effectiveness of the combination of a whole-blood interferon-gamma assay and the tuberculin skin test in detecting latent tuberculosis infection in rheumatoid arthritis patients receiving adalimumab therapy. Arthritis Rheum. 2008 Jun 15;59(6):800-6. (<10 HIV-infected individuals)

12. Clayton R, Grabczynska S, Wilkinson JD. Nodular vasculitis: an indicator for ELISpot screening for tuberculosis? Clin Exp Dermatol. 2007 Nov;32(6):761-2. (<10 HIV-infected individuals)

13. Cobanoglu N, Ozcelik U, Kalyoncu U, Ozen S, Kiraz S, Gurcan N, et al. Interferon-gamma assays for the diagnosis of tuberculosis infection before using tumour necrosis factor-alpha blockers. Int J Tuberc Lung Dis. 2007 Nov;11(11):1177-82. (<10 HIV-infected individuals)

14. Codeluppi M, Cocchi S, Guaraldi G, Di Benedetto F, De Ruvo N, Meacci M, et al. Posttransplant Mycobacterium tuberculosis disease following liver transplantation and the need for cautious evaluation of Quantiferon TB GOLD results in the transplant setting: a case report. Transplant Proc. 2006 May;38(4):1083-5. (<10 HIV-infected individuals)

15. Converse PJ, Jones SL, Astemborski J, Vlahov D, Graham NM. Comparison of a tuberculin interferon-gamma assay with the tuberculin skin test in high-risk adults: effect of human immunodeficiency virus infection. J Infect Dis. 1997 Jul;176(1):144-50. (Older generation IGRA)

16. Damaschin O, Dahmani O, Faibis F, Demachy MC, Abtahi M, Cucherousset N, et al. Esophageal tuberculosis in a patient on maintenance dialysis: advantages of interferon-gamma release assay. Ren Fail. 2009;31(3):248-50. (<10 HIV-infected individuals)

17. Davarpanah M, Rasti M, Mehrabani D, Allahyari S, Neirami R, Saberi-Firoozi. Association between PPD and QuantiFERON Gold TB test in TB infection and disease among HIV infected individuals in southern Iran. Iranian Red Crescent Medical Journal 2009;11(1):71-5. (Noncommercial IGRA)

145

18. Davies MA, Connell T, Johannisen C, Wood K, Pienaar S, Wilkinson KA, et al. Detection of tuberculosis in HIV-infected children using an enzyme-linked immunospot assay. AIDS. 2009 May 15;23(8):961-9. (Noncommercial IGRA)

19. Day CL, Mkhwanazi N, Reddy S, Mncube Z, van der Stok M, Klenerman P, et al. Detection of polyfunctional Mycobacterium tuberculosis-specific T cells and association with viral load in HIV-1-infected persons. J Infect Dis. 2008 Apr 1;197(7):990-9. (Noncommercial IGRA)

20. Desai N, Raste Y, Cooke NT, Harland CC. QuantiFERON-TB Gold testing for tuberculosis in psoriasis patients commencing anti-tumour necrosis factor alpha therapy. Br J Dermatol. 2008 May;158(5):1137-8. (<10 HIV-infected individuals)

21. Dewan PK, Grinsdale J, Kawamura LM. Low sensitivity of a whole-blood interferon-gamma release assay for detection of active tuberculosis. Clin Infect Dis. 2007 Jan 1;44(1):69-73. (Data insufficient)

22. Dinser R, Fousse M, Sester U, Albrecht K, Singh M, Kohler H, et al. Evaluation of latent tuberculosis infection in patients with inflammatory arthropathies before treatment with TNF-alpha blocking drugs using a novel flow-cytometric interferon-gamma release assay. Rheumatology (Oxford). 2008 Feb;47(2):212-8. (<10 HIV-infected individuals)

23. Dixon WG, Watson K, Lunt M, Hyrich KL, Silman AJ, Symmons DP. Rates of serious infection, including site-specific and bacterial intracellular infection, in rheumatoid arthritis patients receiving anti-tumor necrosis factor therapy: results from the British Society for Rheumatology Biologics Register. Arthritis Rheum. 2006 Aug;54(8):2368-76. (<10 HIV-infected individuals)

24. Efthimiou P, Sood S. QuantiFERON TB Gold Test: the new standard for screening of latent tuberculosis in patients with rheumatoid arthritis? Ann Rheum Dis. 2007 Feb;66(2):276. (<10 HIV-infected individuals)

25. Endean AL, Barry SM, Young-Min SA. Possible miliary tuberculosis during adalimumab therapy with negative gamma-IFN release assays. Rheumatology (Oxford). 2009 Mar;48(3):319-20. (<10 HIV-infected individuals)

26. Ferrara G, Losi M, D'Amico R, Roversi P, Piro R, Meacci M, et al. Use in routine clinical practice of two commercial blood tests for diagnosis of infection with Mycobacterium tuberculosis: a prospective study. Lancet. 2006 Apr 22;367(9519):1328-34. (Older generation IGRA)

27. Ferrara G, Losi M, Meacci M, Meccugni B, Piro R, Roversi P, et al. Routine hospital use of a new commercial whole blood interferon-gamma assay for the diagnosis of tuberculosis infection. Am J Respir Crit Care Med. 2005 Sep 1;172(5):631-5. (<10 HIV-infected individuals)

28. Gogus F, Gunendi Z, Karakus R, Erdogan Z, Hizel K, Atalay F. Comparison of tuberculin skin test and QuantiFERON-TB gold in tube test in patients with chronic inflammatory diseases living in a tuberculosis endemic population. Clin Exp Med. 2009 Dec 1. (<10 HIV-infected individuals)

29. Goletti D, Carrara S, Vincenti D, Girardi E. T cell responses to commercial mycobacterium tuberculosis-specific antigens in HIV-infected patients. Clin Infect Dis. 2007 Dec 15;45(12):1652-4. (Duplicate data)

30. Greenberg JD, Reddy SM, Schloss SG, Kurucz OS, Bartlett SJ, Abramson SB, et al. Comparison of an in vitro tuberculosis interferon-gamma assay with delayed-type hypersensitivity testing for detection of latent Mycobacterium tuberculosis: a pilot study in rheumatoid arthritis. J Rheumatol. 2008 May;35(5):770-5. (<10 HIV-infected individuals)

146

31. Grimes CZ, Hwang LY, Williams ML, Austin CM, Graviss EA. Tuberculosis infection in drug users: interferon-gamma release assay performance. Int J Tuberc Lung Dis. 2007 Nov;11(11):1183-9. (<10 HIV-infected individuals)

32. Gupta A, Street AC, Macrae FA. Tumour necrosis factor alpha inhibitors: screening for tuberculosis infection in inflammatory bowel disease. Med J Aust. 2008 Feb 4;188(3):168-70. (<10 HIV-infected individuals)

33. Hammond AS, McConkey SJ, Hill PC, Crozier S, Klein MR, Adegbola RA, et al. Mycobacterial T cell responses in HIV-infected patients with advanced immunosuppression. J Infect Dis. 2008 Jan 15;197(2):295-9. (Noncommercial IGRA)

34. Hill PC, Jackson-Sillah DJ, Fox A, Brookes RH, de Jong BC, Lugos MD, et al. Incidence of tuberculosis and the predictive value of ELISPOT and Mantoux tests in Gambian case contacts. PLoS One. 2008;3(1):e1379. (Noncommercial IGRA)

35. Hornum M, Mortensen KL, Kamper AL, Andersen AB. Limitations of the QuantiFERON-TB Gold test in detecting Mycobacterium tuberculosis infection in immunocompromised patients. Eur J Intern Med. 2008 Mar;19(2):137-9. (Case report or series)

36. Hursitoglu M, Cikrikcioglu MA, Tukek T, Beycan I, Ahmedova N, Karacuha S, et al. Acute effect of low-flux hemodialysis process on the results of the interferon-gamma-based QuantiFERON-TB Gold In-Tube test in end-stage renal disease patients. Transpl Infect Dis. 2009 Feb;11(1):28-32. (<10 HIV-infected individuals)

37. Inoue T, Nakamura T, Katsuma A, Masumoto S, Minami E, Katagiri D, et al. The value of QuantiFERON TB-Gold in the diagnosis of tuberculosis among dialysis patients. Nephrol Dial Transplant. 2009 Jul;24(7):2252-7. (<10 HIV-infected individuals)

38. Inui N, Suda T, Chida K. Use of the QuantiFERON-TB Gold test in Japanese patients with sarcoidosis. Respir Med. 2008 Feb;102(2):313-5. (<10 HIV-infected individuals)

39. Itty S, Bakri SJ, Pulido JS, Herman DC, Faia LJ, Tufty GT, et al. Initial results of QuantiFERON-TB Gold testing in patients with uveitis. Eye. 2009 Apr;23(4):904-9. (<10 HIV-infected individuals)

40. Kabeer BS, Sikhamani R, Raja A. Comparison of interferon gamma and interferon gamma-inducible protein-10 secretion in HIV-tuberculosis patients. AIDS. 2009 Dec 10. (Duplicate data)

41. Karam F, Mbow F, Fletcher H, Senghor CS, Coulibaly KD, LeFevre AM, et al. Sensitivity of IFN-gamma release assay to detect latent tuberculosis infection is retained in HIV-infected patients but dependent on HIV/AIDS progression. PLoS One. 2008;3(1):e1441. (Data insufficient)

42. Kim EY, Lim JE, Jung JY, Son JY, Lee KJ, Yoon YW, et al. Performance of the tuberculin skin test and interferon-gamma release assay for detection of tuberculosis infection in immunocompromised patients in a BCG-vaccinated population. BMC Infect Dis. 2009 Dec 15;9(1):207. (<10 HIV-infected individuals)

43. Kleinert S, Kurzai O, Elias J, Marten K, Engelke C, Feuchtenberger M, et al. Comparison of two interferon-gamma release assays and tuberculin skin test for detecting latent tuberculosis in patients with immune-mediated inflammatory diseases. Ann Rheum Dis. 2010 Apr;69(4):782-4. (<10 HIV-infected individuals)

44. Kobashi Y, Fukuda M, Yoshida K, Oka M. An indeterminate QuantiFERON TB-2G response for miliary tuberculosis, due to severe pancytopenia. J Infect Chemother. 2007 Dec;13(6):414-7. (Older generation IGRA)

45. Kobashi Y, Mouri K, Obase Y, Fukuda M, Miyashita N, Oka M. Clinical evaluation of QuantiFERON TB-2G test for immunocompromised patients. Eur Respir J. 2007 Nov;30(5):945-50. (<10 HIV-infected individuals)

46. Kurup SK, Buggage RR, Clarke GL, Ursea R, Lim WK, Nussenblatt RB. Gamma interferon assay as an alternative to PPD skin testing in selected patients with

147

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47. Kwakernaak AJ, Houtman PM, Weel JF, Spoorenberg JP, Jansen TL. A comparison of an interferon-gamma release assay and tuberculin skin test in refractory inflammatory disease patients screened for latent tuberculosis prior to the initiation of a first tumor necrosis factor alpha inhibitor. Clin Rheumatol. 2010 Aug 25. (<10 HIV-infected individuals)

48. Laffitte E, Janssens JP, Roux-Lombard P, Thielen AM, Barde C, Marazza G, et al. Tuberculosis screening in patients with psoriasis before antitumour necrosis factor therapy: comparison of an interferon-gamma release assay vs. tuberculin skin test. Br J Dermatol. 2009 Jun 5. (<10 HIV-infected individuals)

49. Lai CC, Tan CK, Liao CH, Chou CH, Huang YT, Hsueh PR. Diagnosis of pulmonary tuberculosis among dialysis patients by enzyme-linked immunospot assay for interferon-gamma. Nephrol Dial Transplant. 2009 Aug;24(8):2605-6; author reply 6-7. (<10 HIV-infected individuals)

50. Lange B, Vavra M, Kern WV, Wagner D. Indeterminate results of a tuberculosis-specific interferon-gamma release assay in immunocompromised patients. Eur Respir J. 2010 May;35(5):1179-82. (<10 HIV-infected individuals)

51. Lange C, Hellmich B, Ernst M, Ehlers S. Rapid immunodiagnosis of tuberculosis in a woman receiving anti-TNF therapy. Nat Clin Pract Rheumatol. 2007 Sep;3(9):528-34. (<10 HIV-infected individuals)

52. Larsen MV, Sorensen IJ, Thomsen VO, Ravn P. Re-activation of bovine tuberculosis in a patient treated with infliximab. Eur Respir J. 2008 Jul;32(1):229-31. (<10 HIV-infected individuals)

53. Lawn SD, Bangani N, Vogt M, Bekker LG, Badri M, Ntobongwana M, et al. Utility of interferon-gamma ELISPOT assay responses in highly tuberculosis-exposed patients with advanced HIV infection in South Africa. BMC Infect Dis. 2007;7:99. (Noncommercial IGRA)

54. Lee SS, Chou KJ, Su IJ, Chen YS, Fang HC, Huang TS, et al. High prevalence of latent tuberculosis infection in patients in end-stage renal disease on hemodialysis: Comparison of QuantiFERON-TB GOLD, ELISPOT, and tuberculin skin test. Infection. 2009 Apr;37(2):96-102. (<10 HIV-infected individuals)

55. Liebeschuetz S, Bamber S, Ewer K, Deeks J, Pathan AA, Lalvani A. Diagnosis of tuberculosis in South African children with a T-cell-based assay: a prospective cohort study. Lancet. 2004 Dec 18-31;364(9452):2196-203. (Noncommercial IGRA)

56. Lindemann M, Dioury Y, Beckebaum S, Cicinnati VR, Gerken G, Broelsch CE, et al. Diagnosis of tuberculosis infection in patients awaiting liver transplantation. Hum Immunol. 2009 Jan;70(1):24-8. (<10 HIV-infected individuals)

57. Mackensen F, Becker MD, Wiehler U, Max R, Dalpke A, Zimmermann S. QuantiFERON TB-Gold--a new test strengthening long-suspected tuberculous involvement in serpiginous-like choroiditis. Am J Ophthalmol. 2008 Nov;146(5):761-6. (<10 HIV-infected individuals)

58. Maeda T, Banno S, Maeda S, Naniwa T, Hayami Y, Watanabe M, et al. Usefulness and limitations of QuantiFERON-TB Gold in Japanese rheumatoid arthritis patients: proposal to decrease the lower cutoff level for assessing latent tuberculosis infection. Mod Rheumatol. 2009 Sep 25. (<10 HIV-infected individuals)

59. Manuel O, Humar A, Preiksaitis J, Doucette K, Shokoples S, Peleg AY, et al. Comparison of quantiferon-TB gold with tuberculin skin test for detecting latent tuberculosis infection prior to liver transplantation. Am J Transplant. 2007 Dec;7(12):2797-801. (<10 HIV-infected individuals)

148

60. Marques CD, Duarte AL, de Lorena VM, Souza JR, Souza WV, de Miranda Gomes Y, et al. Evaluation of an interferon gamma assay in the diagnosis of latent tuberculosis infection in patients with rheumatoid arthritis. Rheumatol Int. 2009 Apr 11. (<10 HIV-infected individuals)

61. Martin J, Walsh C, Gibbs A, McDonnell T, Fearon U, Keane J, et al. Comparison of interferon-{gamma}-release assays and conventional screening tests before tumour necrosis factor-{alpha} blockade in patients with inflammatory arthritis. Ann Rheum Dis. 2009 Jan 30. (<10 HIV-infected individuals)

62. Martinez LC, Harrison-Balestra C, Caeiro JP, Nousari CH. The role of the QuantiFERON-TB Gold test as screening prior to administration of tumor necrosis factor inhibitors. Arch Dermatol. 2007 Jun;143(6):809-10. (<10 HIV-infected individuals)

63. Matulis G, Juni P, Villiger PM, Gadola SD. Detection of latent tuberculosis in immunosuppressed patients with autoimmune diseases: performance of a Mycobacterium tuberculosis antigen-specific interferon gamma assay. Ann Rheum Dis. 2008 Jan;67(1):84-90. (<10 HIV-infected individuals)

64. Mazurek GH, Weis SE, Moonan PK, Daley CL, Bernardo J, Lardizabal AA, et al. Prospective comparison of the tuberculin skin test and 2 whole-blood interferon-gamma release assays in persons with suspected tuberculosis. Clin Infect Dis. 2007 Oct 1;45(7):837-45. (Older generation IGRA)

65. Murakami S, Takeno M, Kirino Y, Kobayashi M, Watanabe R, Kudo M, et al. Screening of tuberculosis by interferon-gamma assay before biologic therapy for rheumatoid arthritis. Tuberculosis (Edinb). 2009 Mar;89(2):136-41. (<10 HIV-infected individuals)

66. Passalent L, Khan K, Richardson R, Wang J, Dedier H, Gardam M. Detecting latent tuberculosis infection in hemodialysis patients: a head-to-head comparison of the T-SPOT.TB test, tuberculin skin test, and an expert physician panel. Clin J Am Soc Nephrol. 2007 Jan;2(1):68-73. (<10 HIV-infected individuals)

67. Piana F, Codecasa LR, Cavallerio P, Ferrarese M, Migliori GB, Barbarano L, et al. Use of a T-cell-based test for detection of tuberculosis infection among immunocompromised patients. Eur Respir J. 2006 Jul;28(1):31-4. (<10 HIV-infected individuals)

68. Piana F, Ruffo Codecasa L, Baldan R, Miotto P, Ferrarese M, Cirillo DM. Use of T-SPOT.TB in latent tuberculosis infection diagnosis in general and immunosuppressed populations. New Microbiol. 2007 Jul;30(3):286-90. (<10 HIV-infected individuals)

69. Ponce de Leon D, Acevedo-Vasquez E, Alvizuri S, Gutierrez C, Cucho M, Alfaro J, et al. Comparison of an interferon-gamma assay with tuberculin skin testing for detection of tuberculosis (TB) infection in patients with rheumatoid arthritis in a TB-endemic population. J Rheumatol. 2008 May;35(5):776-81. (<10 HIV-infected individuals)

70. Pratt A, Nicholl K, Kay L. Use of the QuantiFERON TB Gold test as part of a screening programme in patients with RA under consideration for treatment with anti-TNF-alpha agents: the Newcastle (UK) experience. Rheumatology (Oxford). 2007 Jun;46(6):1035-6. (<10 HIV-infected individuals)

71. Raby E, Moyo M, Devendra A, Banda J, De Haas P, Ayles H, et al. The effects of HIV on the sensitivity of a whole blood IFN-gamma release assay in Zambian adults with active tuberculosis. PLoS One. 2008;3(6):e2489. (Reference standard lacking)

72. Rangaka MX, Diwakar L, Seldon R, van Cutsem G, Meintjes GA, Morroni C, et al. Clinical, immunological, and epidemiological importance of antituberculosis T cell responses in HIV-infected Africans. Clin Infect Dis. 2007 Jun 15;44(12):1639-46. (Noncommercial IGRA)

73. Ravn P, Munk ME, Andersen AB, Lundgren B, Nielsen LN, Lillebaek T, et al. Reactivation of tuberculosis during immunosuppressive treatment in a patient with

149

a positive QuantiFERON-RD1 test. Scand J Infect Dis. 2004;36(6-7):499-501. (<10 HIV-infected individuals)

74. Richeldi L, Ewer K, Losi M, Hansell DM, Roversi P, Fabbri LM, et al. Early diagnosis of subclinical multidrug-resistant tuberculosis. Ann Intern Med. 2004 May 4;140(9):709-13. (<10 HIV-infected individuals)

75. Richeldi L, Luppi M, Losi M, Luppi F, Potenza L, Roversi P, et al. Diagnosis of occult tuberculosis in hematological malignancy by enumeration of antigen-specific T cells. Leukemia. 2006 Feb;20(2):379-81. (<10 HIV-infected individuals)

76. Schoepfer A, Flogerzi B, Fallegger S, Schaffer T, Mueller S, Nicod L, et al. Comparison of interferon-gamma release assay versus tuberculin skin test for tuberculosis screening in inflammatory bowel disease. Am J Gastroenterol. 2008;103(11):2799-806. (<10 HIV-infected individuals)

77. Sellam J, Hamdi H, Roy C, Baron G, Lemann M, Puechal X, et al. Comparison of in vitro-specific blood tests with tuberculin skin test for diagnosis of latent tuberculosis before anti-TNF therapy. Ann Rheum Dis. 2007 Dec;66(12):1610-5. (<10 HIV-infected individuals)

78. Sester U, Junker H, Hodapp T, Schutz A, Thiele B, Meyerhans A, et al. Improved efficiency in detecting cellular immunity towards M. tuberculosis in patients receiving immunosuppressive drug therapy. Nephrol Dial Transplant. 2006 Nov;21(11):3258-68. (<10 HIV-infected individuals)

79. Sester U, Wilkens H, van Bentum K, Singh M, Sybrecht GW, Schafers HJ, et al. Impaired detection of Mycobacterium tuberculosis immunity in patients using high levels of immunosuppressive drugs. Eur Respir J. 2009 Sep;34(3):702-10. (<10 HIV-infected individuals)

80. Shah SS, McGowan JP, Klein RS, Converse PJ, Blum S, Gourevitch MN. Agreement between Mantoux skin testing and QuantiFERON-TB assay using dual mycobacterial antigens in current and former injection drug users. Med Sci Monit. 2006 Apr;12(4):MT11-6. (<10 HIV-infected individuals)

81. Shovman O, Anouk M, Vinnitsky N, Arad U, Paran D, Litinsky I, et al. QuantiFERON®-TB Gold in the identifi cation of latent tuberculosis infection in rheumatoid arthritis: a pilot study. Int J Tuberc Lung Dis. 2009;13(11):1427-32. (<10 HIV-infected individuals)

82. Silva LC, Silveira GG, Arnone M, Romiti R, Geluk A, Franken KC, et al. Decrease in Mycobacterium tuberculosis specific immune responses in patients with untreated psoriasis living in a tuberculosis endemic area. Arch Dermatol Res. 2009 May;302(4):255-62. (<10 HIV-infected individuals)

83. Silverman MS, Reynolds D, Kavsak PA, Garay J, Daly A, Davis I. Use of an interferon-gamma based assay to assess bladder cancer patients treated with intravesical BCG and exposed to tuberculosis. Clin Biochem. 2007 Aug;40(12):913-5. (<10 HIV-infected individuals)

84. Soborg B, Ruhwald M, Hetland ML, Jacobsen S, Andersen AB, Milman N, et al. Comparison of Screening Procedures for Mycobacterium tuberculosis Infection Among Patients with Inflammatory Diseases. J Rheumatol. 2009 Sep;36(9):1876-84. (<10 HIV-infected individuals)

85. Soysal A, Bahceciler N, Barlan I, Bakir M. Lack of an inverse association between tuberculosis infection and atopy: by T-cell-based immune assay (RD1-ELISpot). Pediatr Allergy Immunol. 2008 Dec;19(8):709-15. (<10 HIV-infected individuals)

86. Spyridis N, Chakraborty R, Sharland M, Heath PT. Early diagnosis of tuberculosis using an INF-gamma assay in a child with HIV-1 infection and a very low CD4 count. Scand J Infect Dis. 2007;39(10):919-21. (Case report or series)

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87. Stavri H, Ene L, Popa GL, Duiculescu D, Murgoci G, Marica C, et al. Comparison of tuberculin skin test with a whole-blood interferon gamma assay and ELISA, in HIV positive children and adolescents with TB. Roum Arch Microbiol Immunol. 2009 Jan-Mar;68(1):14-9. (Older generation IGRA)

88. Strassburg A, Jafari C, Ernst M, Lotz W, Lange C. Rapid diagnosis of pulmonary TB by BAL enzyme-linked immunospot assay in an immunocompromised host. Eur Respir J. 2008 May;31(5):1132-5. (<10 HIV-infected individuals)

89. Takahashi H, Shigehara K, Yamamoto M, Suzuki C, Naishiro Y, Tamura Y, et al. Interferon gamma assay for detecting latent tuberculosis infection in rheumatoid arthritis patients during infliximab administration. Rheumatol Int. 2007 Oct;27(12):1143-8. (<10 HIV-infected individuals)

90. Takase K, Ohno S, Ideguchi H, Murakami S, Takeno M, Ishigatsubo Y. Mycobacterium tuberculosis-specific immunospot assay of pleural exudate mononuclear cells is useful for the exclusion of tuberculous pleuritis in patients with lupus pleuritis. Lupus. 2009 Feb;18(2):175-7. (<10 HIV-infected individuals)

91. Tanaka R, Matsuura H, Kobashi Y, Fujimoto W. Clinical utility of an interferon-gamma-based assay for mycobacterial detection in papulonecrotic tuberculid. Br J Dermatol. 2007 Jan;156(1):169-71. (<10 HIV-infected individuals)

92. Tozlu M, Kalyoncu U, Alp S, Unal S, Calguneri M. Diagnostic accuracy of Quantiferon TB test for patients with SLE and miliary tuberculosis. Rheumatol Int. 2009 Sep;29(11):1395-6. (<10 HIV-infected individuals)

93. Triverio PA, Bridevaux PO, Roux-Lombard P, Niksic L, Rochat T, Martin PY, et al. Interferon-gamma release assays versus tuberculin skin testing for detection of latent tuberculosis in chronic haemodialysis patients. Nephrol Dial Transplant. 2009 Jun;24(6):1952-6. (<10 HIV-infected individuals)

94. Tsiouris SJ, Coetzee D, Toro PL, Austin J, Stein Z, El-Sadr W. Sensitivity analysis and potential uses of a novel gamma interferon release assay for diagnosis of tuberculosis. J Clin Microbiol. 2006 Aug;44(8):2844-50. (HIV by self report)

95. Tubach F, Salmon D, Ravaud P, Allanore Y, Goupille P, Breban M, et al. Risk of tuberculosis is higher with anti-tumor necrosis factor monoclonal antibody therapy than with soluble tumor necrosis factor receptor therapy: The three-year prospective French Research Axed on Tolerance of Biotherapies registry. Arthritis Rheum. 2009 Jul;60(7):1884-94. (<10 HIV-infected individuals)

96. Vassilopoulos D, Stamoulis N, Hadziyannis E, Archimandritis AJ. Usefulness of enzyme-linked immunosorbent assay (Elispot) compared to tuberculin skin testing for latent tuberculosis screening in rheumatic patients scheduled for anti-tumor necrosis factor treatment. Addendum. J Rheumatol. 2008 Jul;35(7):1464. (<10 HIV-infected individuals)

97. Vincenti D, Carrara S, Butera O, Bizzoni F, Casetti R, Girardi E, et al. Response to region of difference 1 (RD1) epitopes in human immunodeficiency virus (HIV)-infected individuals enrolled with suspected active tuberculosis: a pilot study. Clin Exp Immunol. 2007 Oct;150(1):91-8. (Reference standard lacking)

98. Winthrop KL, Daley CL. A novel assay for screening patients for latent tuberculosis infection prior to anti-TNF therapy. Nat Clin Pract Rheumatol. 2008 Sep;4(9):456-7. (<10 HIV-infected individuals)

99. Winthrop KL, Nyendak M, Calvet H, Oh P, Lo M, Swarbrick G, et al. Interferon-gamma release assays for diagnosing mycobacterium tuberculosis infection in renal dialysis patients. Clin J Am Soc Nephrol. 2008 Sep;3(5):1357-63. (<10 HIV-infected individuals)

100. Ye LP, Liang Y, Shi B, Liu LH, Jin JG, Zhang YZ, et al. Implication of ELISPOT assay for diagnosis of tuberculosis in sputum-negative patients with hematologic diseases.

151

Chinese Journal of Infection and Chemotherapy. 2010;10(1):44-8. (<10 HIV-infected individuals)

152

Annex 6. Selection of studies evaluating the use of IGRAs for tuberculosis screening of health care workers

IGRA studies identified

from electronic databases sources n=546

IGRA studies with Health Care Workers

n=56

N=

Unique studies included in final

review

n=48

IGRA studies not done in health care workers

n=490

Unpublished articles and conference

presentations eligible for inclusion

n=4

Did not meet eligibility criteria n=12

(point source outbreaks (7), treatment monitoring (2),

short term reproducibility (3))

153

Included studies 1. Pai M, Joshi R, Dogra S, et al. Serial testing of health care workers for tuberculosis

using interferon-gamma assay. Am J Respir Crit Care Med. 2006;174:349-55. 2. Pai M, Gokhale K, Joshi R, et al. Mycobacterium tuberculosis infection in health care

workers in rural India: comparison of a whole-blood, interferon-g assay with tuberculin skin testing. JAMA. 2005;293:2746-55.

3. Drobniewski F, Balabanova Y, Zakamova E, et al. Rates of Latent Tuberculosis in Health Care Staff in Russia. PLoS Med. 2007;4:e55.

4. Lien LT, Hang NT, Kobayashi N, et al. Prevalence and risk factors for tuberculosis infection among hospital workers in Hanoi, Viet Nam. PLoS ONE. 2009;4:e6798.

5. Demkow U, Broniarek-Samson B, Filewska M, et al. Prevalence of latent tuberculosis infection in health care workers in Poland assessed by interferon-gamma whole blood and tuberculin skin tests. J Physiol Pharmacol. 2008;59 Suppl 6:209-17.

6. Dorman S, Belknap R, Weinfurter P, et al. Evaluation of New Interferon-Gamma Release Assays (IGRAs) in the Diagnosis of Latent Tuberculosis Infection in U.S. Health Care Workers: Baseline Testing Results. American Thoracic Society 2009; Sunday May 15, 2009; San Diego, USA: Am J Respir Crit Care Med; 2009. p. A1010.

7. Mehta SR, MacGruder C, Looney D, et al. Differences in tuberculin reactivity as determined in a veterans administration employee health screening program. Clin Vaccine Immunol. 2009;16:541-3.

8. Topic RZ, Dodig S, Zoricic-Letoja I. Interferon-gamma and immunoglobulins in latent tuberculosis infection. Arch Med Res. 2009;40:103-8.

9. Barsegian V, Mathias KD, Wrighton-Smith P, et al. Prevalence of latent tuberculosis infection in German radiologists. J Hosp Infect. 2008.

10. Carvalho AC, Crotti N, Crippa M, et al. QuantiFERON((R))-TB Gold test for healthcare workers. J Hosp Infect. 2008.

11. Ciaschetti A, Franchi A, Richeldi L, et al. [Screening of latent tuberculosis infection in health care workers by QuantiFERON-TB and tuberculin skin test]. G Ital Med Lav Ergon. 2007;29:406-7.

12. Harada N, Nakajima Y, Higuchi K, et al. Screening for tuberculosis infection using whole-blood interferon-gamma and Mantoux testing among Japanese healthcare workers. Infect Control Hosp Epidemiol. 2006;27:442-8.

13. Hotta K, Ogura T, Nishii K, et al. Whole blood interferon-gamma assay for baseline tuberculosis screening among Japanese healthcare students. PLoS ONE. 2007;2:e803.

14. Nienhaus A, Schablon A, Bacle CL, et al. Evaluation of the interferon-gamma release assay in healthcare workers. Int Arch Occup Environ Health. 2008;81:295-300.

15. Nienhaus A, Loddenkemper R, Hauer B, et al. [Latent tuberculosis infection in healthcare workers--evaluation of an Interferon-gamma release assay]. Pneumologie. 2007;61:219-23.

16. Nienhaus A, Schablon A, Loddenkemper R, et al. [Prevalence of latent tuberculosis infection in healthcare workers in geriatric care]. Pneumologie. 2007;61:613-6.

17. Schablon A, Beckmann G, Harling M, et al. Prevalence of Latent Tuberculosis Infection among Health Care Workers in a hospital for pulmonary diseases. J Occup Med Toxicol. 2009;4:1.

18. Soborg B, Andersen AB, Larsen HK, et al. Detecting a low prevalence of latent tuberculosis among health care workers in Denmark detected by M. tuberculosis specific IFN-gamma whole-blood test. Scand J Infect Dis. 2007;39:554-9.

19. Stebler A, Iseli P, Muhlemann K, et al. Whole-blood interferon-gamma release assay for baseline tuberculosis screening of healthcare workers at a swiss university hospital. Infect Control Hosp Epidemiol. 2008;29:681-3.

154

20. Thijsen SF, van Rossum SV, Arend S, et al. The Value of Interferon Gamma Release Assays for Diagnosis Infection With Mycobacterium Tuberculosis During an Annual Screening of Health Care Workers. J Occup Environ Med. 2008;50:1207-8.

21. Veeser PI, Smith PK, Handy B, et al. Tuberculosis screening on a health science campus: use of QuantiFERON-TB Gold Test for students and employees. J Am Coll Health. 2007;56:175-80.

22. Vinton P, Mihrshahi S, Johnson P, et al. Comparison of QuantiFERON-TB Gold In-Tube Test and Tuberculin Skin Test for Identification of Latent Mycobacterium tuberculosis Infection in Healthcare Staff and Association Between Positive Test Results and Known Risk Factors for Infection. Infect Control Hosp Epidemiol. 2009.

23. Kang YA, Lee HW, Yoon HI, et al. Discrepancy between the tuberculin skin test and the whole-blood interferon gamma assay for the diagnosis of latent tuberculosis infection in an intermediate tuberculosis-burden country. JAMA. 2005;293:2756-61.

24. Ozekinci T, Ozbek E, Celik Y. Comparison of tuberculin skin test and a specific T-cell-based test, T-Spot.TB, for the diagnosis of latent tuberculosis infection. J Int Med Res. 2007;35:696-703.

25. Choi JC, Shin JW, Kim JY, et al. The effect of previous tuberculin skin test on the follow-up examination of whole-blood interferon-gamma assay in the screening for latent tuberculosis infection. Chest. 2008;133:1415-20.

26. Khanna P, Nikolayevskyy V, Warburton F, et al. Rate of latent tuberculosis infection detected by occupational health screening of nurses new to a london teaching hospital. Infect Control Hosp Epidemiol. 2009;30:581-4.

27. Alvarez-Leon EE, Espinosa-Vega E, Santana-Rodriguez E, et al. Screening for tuberculosis infection in spanish healthcare workers: Comparison of the QuantiFERON-TB gold in-tube test with the tuberculin skin test. Infect Control Hosp Epidemiol. 2009;30:876-83.

28. Casas I, Latorre I, Esteve M, et al. Evaluation of interferon-gamma release assays in the diagnosis of recent tuberculosis infection in health care workers. PLoS ONE. 2009;4:e6686.

29. Eum SY, Lee YJ, Kwak HK, et al. Evaluation of the diagnostic utility of a whole-blood interferon-gamma assay for determining the risk of exposure to Mycobacterium tuberculosis in Bacille Calmette-Guerin (BCG)-vaccinated individuals. Diagn Microbiol Infect Dis. 2008.

30. Fox BD, Kramer MR, Mor Z, et al. The QuantiFERON((R))-TB-GOLD Assay for Tuberculosis Screening in Healthcare Workers: A Cost-Comparison Analysis. Lung. 2009.

31. Zhao X, Mazlagic D, Flynn EA, et al. Is the QuantiFERON-TB blood assay a good replacement for the tuberculin skin test in tuberculosis screening? a pilot study at Berkshire Medical Center. Am J Clin Pathol. 2009;132:678-86.

32. Girardi E, Angeletti C, Puro V, et al. Estimating diagnostic accuracy of tests for latent tuberculosis infection without a gold standard among healthcare workers. Euro Surveill. 2009;14.

33. Cummings KJ, Smith TS, Shogren ES, et al. Prospective comparison of tuberculin skin test and QuantiFERON-TB Gold In-Tube assay for the detection of latent tuberculosis infection among healthcare workers in a low-incidence setting. Infect Control Hosp Epidemiol. 2009;30:1123-6.

34. Mirtskhulava V, Kempker R, Shields KL, et al. Prevalence and risk factors for latent tuberculosis infection among health care workers in Georgia. The International Journal of Tuberculosis and Lung Disease. 2008;12:513-9.

155

35. Torres Costa J, Sa R, Cardoso MJ, et al. Tuberculosis screening in Portuguese healthcare workers using the tuberculin skin test and the interferon-{gamma} release assay. Eur Respir J. 2009;34:1423-8.

36. Joshi R, Gajalakshmi D, Reddy MVR, et al. Unstable IGRA conversions and reversions over three time points among medical students in a high burden setting. 2nd Global Symposium on IGRAs; May 30, 2009; Dubrovnik, Croatia2009.

37. Belknap R, Feske M, Choung G, et al. Diagnosis of Latent Tuberculosis Infection in Health Care Workers: Impact of a recent Tuberculin Skin Test on the Interferon-gamma Release Assays (IGRAs). American Thoracic Society 2009; Sunday May 17, 2009; San Diego, USA: Am J Respir Crit Care Med; 2009. p. A1011.

38. Zwerling A, Cloutier-Ladurantaye J, Pietrangelo F, et al. Conversions and Reversions in Health Care Workers in Montreal, Canada Using QuantiFERON-TB-Gold In-Tube. American Thoracic Society 2009; Sunday May 17, 2009; San Diego, USA: Am J Respir Crit Care Med; 2009. p. A1012.

39. Chee CB, Lim LK, Barkham TM, et al. Use of a T cell interferon-gamma release assay to evaluate tuberculosis risk in newly qualified physicians in Singapore healthcare institutions. Infect Control Hosp Epidemiol. 2009;30:870-5.

40. Yoshiyama T, Harada N, Higuchi K, et al. Estimation of incidence of tuberculosis infection in health-care workers using repeated interferon-gamma assays. Epidemiol Infect. 20091-8.

41. Lee K, Han MK, Choi HR, et al. Annual incidence of latent tuberculosis infection among newly employed nurses at a tertiary care university hospital. Infect Control Hosp Epidemiol. 2009;30:1218-22.

42. de Perio MA, Tsevat J, Roselle GA, et al. Cost-effectiveness of Interferon Gamma Release Assays vs Tuberculin Skin Tests in Health Care Workers. Arch Intern Med. 2009;169:179-87.

43. Linertova R, Alvarez-Leon EE, Garcia-Perez L, et al. Costs of QuantiFERON-TB Gold versus tuberculin skin test in Spanish healthcare workers. J Hosp Infect.75:52-5.

44. Sahni R, Miranda C, Yen-Lieberman B, et al. Does the Implementation of an Interferon-gamma Release Assay in Lieu of a Tuberculin Skin Test Increase Acceptance of Preventive Therapy for Latent Tuberculosis Among Healthcare Workers? Infect Control Hosp Epidemiol. 2009.

45. Costa JT, Silva R, Sa R, et al. Comparison of interferon-gamma release assay and tuberculin test for screening in healthcare workers. Rev Port Pneumol.16:211-21.

46. Pollock NR, Kashino SS, Napolitano DR, et al. Evaluation of the effect of treatment of latent tuberculosis infection on QuantiFERON-TB gold assay results. Infect Control Hosp Epidemiol. 2009;30:392-5.

47. Budnick LD, Burday M, Brachman G, Mangura CT, DeBlock D, Lardizabal A. Blood assay for tuberculosis: initial findings in a preplacement surveillance program. J Occup Environ Med. 2006 Nov;48(11):1115-7.

48. Miranda C, Yen-Lieberman B, Terpeluk P, Tomford JW, Gordon S. Reducing the rates of indeterminate results of the QuantiFERON-TB Gold In-Tube test during routine preemployment screening for latent tuberculosis infection among healthcare personnel. Infect Control Hosp Epidemiol. 2009 Mar;30(3):296-8.

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1. Veerapathran A, Joshi R, Goswami K, Dogra S, Moodie EEM, Reddy MVR, et al. T-Cell Assays for Tuberculosis Infection: Deriving Cut-Offs for Conversions Using Reproducibility Data. PLoS ONE. 2008 03/26;3(3):e1850. (short term reproducibility)

2. Detjen AK, Loebenberg L, Grewal HM, Stanley K, Gutschmidt A, Kruger C, et al. Short-term Reproducibility of a Commercial Interferon-gamma Release Assay. Clin Vaccine Immunol. 2009 Jun 17. (short term reproducibility)

3. van Zyl-Smit RN, Pai M, Peprah K, Meldau R, Kieck J, Juritz J, et al. Within-subject Variability and Boosting of T Cell IFN-{gamma} Responses Following Tuberculin Skin Testing. Am J Respir Crit Care Med. 2009 Apr 16. (short term reproducibility)

4. Lee SJ, Kim HS, Jung Eun Ma, Sang Min Lee, HyunSeok Ham, Cho YJ, et al. Tuberculin Skin Test and QuantiFERON-TB Gold Assay before and after Treatment for Latent Tuberculosis Infection among Health Care Workers in Local Tertiary Hospital. Tuberculosis & Respiratory Diseases. 2007 April 2007;62(4):270-6. (Treatment monitoring)

5. Pai M, Joshi R, Dogra S, Mendiratta DK, Narang P, Dheda K, et al. Persistently elevated T cell interferon-gamma responses after treatment for latent tuberculosis infection among health care workers in India: a preliminary report. J Occup Med Toxicol. 2006;1:7. (Treatment monitoring)

6. Herrmann JL, Simonney N, Bergeron A, Ducreux-Adolphe N, Porcher R, Rouveau M, et al. IFNgamma and antibody responses among French nurses during a tuberculosis contact tracing investigation. Pathol Biol (Paris). 2008 Apr 3. (Contact investigation/ point source outbreaks)

7. Kobashi Y, Obase Y, Fukuda M, Yoshida K, Miyashita N, Fujii M, et al. Usefulness of QuantiFERON TB-2G, a diagnostic method for latent tuberculosis infection, in a contact investigation of health care workers. Internal medicine (Tokyo, Japan). 2007;46(18):1543-9. (Contact investigation/ point source outbreaks)

8. Lee SS-J, LIU Y-C, HUANG T-S, CHEN Y-S, TSAI H-C, WANN S-R, et al. Comparison of the interferon- g release assay and the tuberculin skin test for contact investigation of tuberculosis in BCG-vaccinated health care workers. Scandinavian journal of infectious diseases. 2007:1-8. (Contact investigation/ point source outbreaks)

9. Ringshausen FC, Schlosser S, Nienhaus A, Schablon A, Schultze-Werninghaus G, Rohde G. In-hospital contact investigation among health care workers after exposure to smear-negative tuberculosis. J Occup Med Toxicol. 2009 Jun 8;4(1):11. (Contact investigation/ point source outbreaks)

10. Storla DG, Kristiansen I, Oftung F, Korsvold GE, Gaupset M, Gran G, et al. Use of interferon gamma-based assay to diagnose tuberculosis infection in health care workers after short term exposure. BMC Infect Dis. 2009;9:60. (Contact investigation/ point source outbreaks)

11. Tripodi D, Brunet-Courtois B, Nael V, Audrain M, Chailleux E, Germaud P, et al. Evaluation of the tuberculin skin test and the interferon-gamma release assay for TB screening in French healthcare workers. J Occup Med Toxicol. 2009;4:30. (Contact investigation/ point source outbreaks)

12. Vinci MR, Russo C, Zaffina S, di Felice C, Menichella D, Pietroiusti A. [Role of screening tests for indirect diagnosis of tuberculosis in health care workers: Mantoux and the new tests on blood ELISA]. Giornale italiano di medicina del lavoro ed ergonomia. 2007 Jul-Sep;29(3 Suppl):399-401. (Contact investigation/ point source outbreaks)

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Annex 7. Selection of studies evaluating the use of IGRAs LTBI screening in contact and outbreak investigations

Included studies 1. Adetifa IM, Lugos MD, Hammond A, Jeffries D, Donkor S, Adegbola RA, et al.

Comparison of Two Interferon Gamma Release Assays in the diagnosis of Mycobacterium tuberculosis infection and disease in The Gambia. BMC Infect Dis. 2007 Oct 25;7(1):122.

2. Adetifa IM, Ota MO, Jeffries DJ, Hammond A, Lugos MD, Donkor S, et al. Commercial interferon gamma release assays compared to the tuberculin skin test for diagnosis of latent Mycobacterium tuberculosis infection in childhood contacts in the Gambia. Pediatr Infect Dis J. May;29(5):439-43.

3. Hansted E, Andriuskeviciene A, Sakalauskas R, Kevalas R, Sitkauskiene B. T-cell-based diagnosis of tuberculosis infection in children in Lithuania: a country of high

158

incidence despite a high coverage with bacille Calmette-Guerin vaccination. BMC Pulm Med. 2009 Aug 18;9(1):41.

4. Hesseling AC, Mandalakas AM, Kirchner LH, Chegou NN, Marais BJ, Zhu X, et al. Highly Discordant T-Cell Responses In Individuals With Recent Household Tuberculosis Exposure. Thorax. 2008 Aug 5.

5. Lee SS-J, LIU Y-C, HUANG T-S, CHEN Y-S, TSAI H-C, WANN S-R, et al. Comparison of the interferon- g release assay and the tuberculin skin test for contact investigation of tuberculosis in BCG-vaccinated health care workers. Scandinavian journal of infectious diseases. 2007:1-8.

6. Machado A, Jr., Emodi K, Takenami I, Finkmoore BC, Barbosa T, Carvalho J, et al. Analysis of discordance between the tuberculin skin test and the interferon-gamma release assay. Int J Tuberc Lung Dis. 2009 Apr;13(4):446-53.

7. Nakaoka H, Lawson L, Squire B, Coulter B, Ravn P, Brock I, et al. Risk for tuberculosis among children. Emerg Infect Dis. 2006;12(9):1383-88.

8. Nicol MP, Davies MA, Wood K, Hatherill M, Workman L, Hawkridge A, et al. Comparison of T-SPOT.TB assay and tuberculin skin test for the evaluation of young children at high risk for tuberculosis in a community setting. Pediatrics. 2009 Jan;123(1):38-43.

9. Okada K, Mao TE, Mori T, Miura T, Sugiyama T, Yoshiyama T, et al. Performance of an interferon-gamma release assay for diagnosing latent tuberculosis infection in children. Epidemiol Infect. 2007 Nov 8:1-9.

10. Ozekinci T, Ozbek E, Celik Y. Comparison of tuberculin skin test and a specific T-cell-based test, T-Spot.TB, for the diagnosis of latent tuberculosis infection. The Journal of international medical research. 2007 Sep-Oct;35(5):696-703.

11. Pai M, Joshi R, Dogra S, Zwerling AA, Gajalakshmi D, Goswami K, et al. T-cell assay conversions and reversions among household contacts of tuberculosis patients in rural India. The International Journal of Tuberculosis and Lung Disease. 2009;13:84-92.

12. Petrucci R, Abu Amer N, Gurgel RQ, Sherchand JB, Doria L, Lama C, et al. Interferon gamma, interferon-gamma-induced-protein 10, and tuberculin responses of children at high risk of tuberculosis infection. Pediatr Infect Dis J. 2008 Dec;27(12):1073-7.

13. Ruhwald M, Petersen J, Kofoed K, Nakaoka H, Cuevas LE, Lawson L, et al. Improving T-cell assays for the diagnosis of latent TB infection: potential of a diagnostic test based on IP-10. PLoS ONE. 2008;3(8):e2858.

14. Tsiouris SJ, Austin J, Toro P, Coetzee D, Weyer K, Stein Z, et al. Results of a tuberculosis-specific IFN-gamma assay in children at high risk for tuberculosis infection. Int J Tuberc Lung Dis. 2006 Aug;10(8):939-41.

15. Shanaube. ZAMSTAR study: preliminary results. FIND: Report for WHO Expert Group Meeting on IGRAs. 2010 (Unpublished).

16. Kassambira T, Shah M, Adrian P, Holshouser M, Madhi S, Chaisson R, et al. QuantiFERON-TB Gold IN-Tube for Diagnosis of M. tuberculosis infection in Children with Adult Household Tuberculosis Contact. 2010 (unpublished).

159


1. Ahmed S, Newton A, Allison T. Tuberculosis in a Yorkshire prison: case report. Euro Surveill. 2007 Sep;12(9):E13-4. (High-income country setting)

2. Anderson ST, Williams AJ, Brown JR, Newton SM, Simsova M, Nicol MP, et al. Transmission of Mycobacterium Tuberculosis Undetected by Tuberculin Skin Testing. Am J Respir Crit Care Med. 2006 Feb 2. (High-income country setting)

3. Arend SM, Thijsen SF, Leyten EM, Bouwman JJ, Franken WP, Koster BF, et al. Comparison of two interferon-gamma assays and tuberculin skin test for tracing tuberculosis contacts. Am J Respir Crit Care Med. 2007 Mar 15;175(6):618-27. (High-income country setting)

4. Bakir M, Millington KA, Soysal A, Deeks JJ, Efee S, Aslan Y, et al. Prognostic value of a T-cell-based, interferon-gamma biomarker in children with tuberculosis contact. Annals of internal medicine. 2008 Dec 2;149(11):777-87. (Non Commercial Assay)

5. Bittmann S. Large scale screening for tuberculosis at a metropolitan university Victorian Infectious Diseases Bulletin. 2003 December 2003;6(4):80-1. (High-income country setting)

6. Brock I, Ruhwald M, Lundgren B, Westh H, Mathiesen LR, Ravn P. Latent tuberculosis in HIV positive, diagnosed by the M. tuberculosis specific interferon-gamma test. Respir Res. 2006;7:56. (High-income country setting)

7. Brock I, Weldingh K, Lillebaek T, Follmann F, Andersen P. Comparison of tuberculin skin test and new specific blood test in tuberculosis contacts. Am J Respir Crit Care Med. 2004 Jul 1;170(1):65-9. (High-income country setting)

8. Brodie D, Lederer DJ, Gallardo JS, Trivedi SH, Burzynski JN, Schluger NW. Use of an Interferon-{gamma} Release Assay to Diagnose Latent Tuberculosis Infection in the Foreign-born. Chest. 2008 Jan 15. (High-income country setting)

9. Chee CB, Barkham TM, Khinmar KW, Gan SH, Wang YT. Quantitative T-cell interferon-gamma responses to Mycobacterium tuberculosis-specific antigens in active and latent tuberculosis. Eur J Clin Microbiol Infect Dis. 2009 Jun;28(6):667-70. (High-income country setting)

10. Choi CM, Hwang SS, Lee CH, Lee HW, Kang CI, Kim CH, et al. Latent tuberculosis infection in a military setting diagnosed by whole-blood interferon-gamma assay. Respirology (Carlton, Vic. 2007 Nov;12(6):898-901. (High-income country setting)

11. Chun JK, Kim CK, Kim HS, Jung GY, Lee TJ, Kim KH, et al. The role of a whole blood interferon-gamma assay for the detection of latent tuberculosis infection in Bacille Calmette-Guerin vaccinated children. Diagnostic microbiology and infectious disease. 2008 Dec;62(4):389-94. (High-income country setting)

12. Codecasa LR, Ferrarese M, Penati V, Lacchini C, Cirillo D, Scarparo C, et al. Comparison of tuberculin skin test and Quantiferon immunological assay for latent tuberculosis infection. Monaldi Arch Chest Dis. 2005 Sep;63(3):158-62. (High-income country setting)

13. del Corral H, ParÃs SC, MarÃn ND, MarÃn DM, LÃ³pez L, Henao HM, et al. IFNÎ³ Response to <italic>Mycobacterium tuberculosis</italic>, Risk of Infection and Disease in Household Contacts of Tuberculosis Patients in Colombia. PLoS ONE. 2009;4(12):e8257. (Non Commercial Assay)

14. Diel R, Ernst M, Doscher G, Visuri-Karbe L, Greinert U, Niemann S, et al. Avoiding the effect of BCG vaccination in detecting Mycobacterium tuberculosis infection with a blood test. Eur Respir J. 2006 Jul;28(1):16-23. (High-income country setting)

15. Diel R, Loddenkemper R, Meywald-Walter K, Gottschalk R, Nienhaus A. Comparative Performance of Tuberculin Skin Test, QuantiFERON-TB-Gold In Tube Assay, and T-

160

Spot.TB Test in Contact Investigations for Tuberculosis. Chest. 2008 Nov 18. (High-income country setting)

16. Diel R, Loddenkemper R, Meywald-Walter K, Niemann S, Nienhaus A. Predictive value of a whole blood IFN-gamma assay for the development of active tuberculosis disease after recent infection with Mycobacterium tuberculosis. Am J Respir Crit Care Med. 2008 May 15;177(10):1164-70. (High-income country setting)

17. Diel R, Nienhaus A, Lange C, Meywald-Walter K, Forssbohm M, Schaberg T. Tuberculosis contact investigation with a new, specific blood test in a low-incidence population containing a high proportion of BCG-vaccinated persons. Respir Res. 2006;7:77. (High-income country setting)

18. Doherty TM, Demissie A, Olobo J, Wolday D, Britton S, Eguale T, et al. Immune responses to the Mycobacterium tuberculosis-specific antigen ESAT-6 signal subclinical infection among contacts of tuberculosis patients. J Clin Microbiol. 2002 Feb;40(2):704-6. (High-income country setting)

19. Dominguez J, Ruiz-Manzano J, De Souza-Galvao M, Latorre I, Mila C, Blanco S, et al. Comparison of two commercially available gamma interferon blood tests for immunodiagnosis of tuberculosis. Clin Vaccine Immunol. 2008 Jan;15(1):168-71. (High-income country setting)

20. Eisenhut M, Paranjothy S, Abubakar I, Bracebridge S, Lilley M, Mulla R, et al. BCG vaccination reduces risk of infection with Mycobacterium tuberculosis as detected by gamma interferon release assay. Vaccine. 2009 Oct 19;27(44):6116-20. (High-income country setting)

21. Ewer K, Deeks J, Alvarez L, Bryant G, Waller S, Andersen P, et al. Comparison of T-cell-based assay with tuberculin skin test for diagnosis of Mycobacterium tuberculosis infection in a school tuberculosis outbreak. Lancet. 2003 Apr 5;361(9364):1168-73. (High-income country setting)

22. Ewer K, Millington KA, Deeks JJ, Alvarez L, Bryant G, Lalvani A. Dynamic Antigen-specific T-Cell Responses after Point-Source Exposure to Mycobacterium tuberculosis. Am J Respir Crit Care Med. 2006 Oct 1;174(7):831-9. (High-income country setting)

23. Franken WP, Koster BF, Bossink AW, Thijsen SF, Bouwman JJ, van Dissel JT, et al. Follow-up study of tuberculosis-exposed supermarket customers with negative tuberculin skin test results in association with positive gamma interferon release assay results. Clin Vaccine Immunol. 2007 Sep;14(9):1239-41. (High-income country setting)

24. Girardi E, Loffredo M, Alessandrini A, Anzidei G, Goletti D. A two-step approach for screening contacts of active tuberculosis. Infection. 2007 Apr;35(2):122-3. (High-income country setting)

25. Goletti D, Parracino MP, Butera O, Bizzoni F, Casetti R, Dainotto D, et al. Isoniazid prophylaxis differently modulates T-cell responses to RD1-epitopes in contacts recently exposed to Mycobacterium tuberculosis: a pilot study. Respir Res. 2007 Jan 27;8(1):5. (High-income country setting)

26. Grare M, Derelle J, Dailloux M, Laurain C. QuantiFERON-TB Gold In-Tube as help for the diagnosis of tuberculosis in a French pediatric hospital. Diagnostic microbiology and infectious disease. Apr;66(4):366-72. (High-income country setting)

27. Harada N, Higuchi K, Mori T. Assessment of nosocomial transmission of tuberculosis in a psychiatric hospital using a whole blood interferon-gamma assay. Japanese journal of infectious diseases. 2008 Sep;61(5):415-8. (High-income country setting)

28. Herrmann JL, Belloy M, Porcher R, Simonney N, Aboutaam R, Lebourgeois M, et al. Temporal dynamics of interferon gamma responses in children evaluated for tuberculosis. PLoS ONE. 2009;4(1):e4130. (High-income country setting)

161

29. Herrmann JL, Simonney N, Bergeron A, Ducreux-Adolphe N, Porcher R, Rouveau M, et al. IFNgamma and antibody responses among French nurses during a tuberculosis contact tracing investigation. Pathol Biol (Paris). 2008 Apr 3. (High-income country setting)

30. Higuchi K, Harada N, Fukazawa K, Mori T. Relationship between whole-blood interferon-gamma responses and the risk of active tuberculosis. Tuberculosis (Edinb). 2008 Feb 20. (High-income country setting)

31. Higuchi K, Harada N, Mori T, Sekiya Y. Use of QuantiFERON-TB Gold to investigate tuberculosis contacts in a high school. Respirology (Carlton, Vic.) 2007 Jan;12(1):88-92. (High-income country setting)

32. Higuchi K, Kondo S, Wada M, Hayashi S, Ootsuka G, Sakamoto N, et al. Contact investigation in a primary school using a whole blood interferon-gamma assay. J Infect. 2009 Mar 31. (High-income country setting)

33. Hill PC, Brookes RH, Adetifa IM, Fox A, Jackson-Sillah D, Lugos MD, et al. Comparison of enzyme-linked immunospot assay and tuberculin skin test in healthy children exposed to Mycobacterium tuberculosis. Pediatrics. 2006 May;117(5):1542-8. (Non Commercial Assay)

34. Hill PC, Brookes RH, Fox A, Fielding K, Jeffries DJ, Jackson-Sillah D, et al. Large-scale evaluation of enzyme-linked immunospot assay and skin test for diagnosis of Mycobacterium tuberculosis infection against a gradient of exposure in The Gambia. Clin Infect Dis. 2004 Apr 1;38(7):966-73. (Non Commercial Assay)

35. Hill PC, Brookes RH, Fox A, Jackson-Sillah D, Jeffries DJ, Lugos MD, et al. Longitudinal Assessment of an ELISPOT Test for Mycobacterium tuberculosis Infection. PLoS Med. 2007 Jun 12;4(6):e192. (Non Commercial Assay)

36. Hill PC, Brookes RH, Fox A, Jackson-Sillah D, Lugos MD, Jeffries DJ, et al. Surprisingly High Specificity of the PPD Skin Test for M. tuberculosis Infection from Recent Exposure in The Gambia. PLoS ONE. 2006;1:e68. (Non Commercial Assay)

37. Hill PC, Fox A, Jeffries DJ, Jackson-Sillah D, Lugos MD, Owiafe PK, et al. Quantitative T cell assay reflects infectious load of Mycobacterium tuberculosis in an endemic case contact model. Clin Infect Dis. 2005 Jan 15;40(2):273-8. (Non Commercial Assay)

38. Hill PC, Jackson-Sillah DJ, Fox A, Brookes RH, de Jong BC, Lugos MD, et al. Incidence of Tuberculosis and the Predictive Value of ELISPOT and Mantoux Tests in Gambian Case Contacts. PLoS ONE. 2008;3(1):e1379. (Non Commercial Assay)

39. Hill PC, Jeffries DJ, Brookes RH, Fox A, Jackson-Sillah D, Lugos MD, et al. Using ELISPOT to Expose False Positive Skin Test Conversion in Tuberculosis Contacts. PLoS ONE. 2007;2:e183. (Non Commercial Assay)

40. Hussain R, Talat N, Shahid F, Dawood G. Biomarker changes associated with Tuberculin Skin Test (TST) conversion: a two-year longitudinal follow-up study in exposed household contacts. PLoS ONE. 2009;4(10):e7444. (Non Commercial Assay)

41. Jackson-Sillah D, Hill PC, Fox A, Brookes RH, Donkor SA, Lugos MD, et al. Screening for tuberculosis among 2381 household contacts of sputum-smear-positive cases in The Gambia. Transactions of the Royal Society of Tropical Medicine and Hygiene. 2007 Jun;101(6):594-601. (Non Commercial Assay)

42. Janssens JP, Roux-Lombard P, Perneger T, Metzger M, Vivien R, Rochat T. Contribution of a IFN-gamma assay in contact tracing for tuberculosis in a low-incidence, high immigration area. Swiss Med Wkly. 2008 Oct 4;138(39-40):585-93. (High-income country setting)

43. Janssens JP. Interferon-gamma release assay tests to rule out active tuberculosis. Eur Respir J. 2007 Jul;30(1):183-4; author reply 4-5. (High-income country setting)

162

44. Jeffries DJ, Hill PC, Fox A, Lugos M, Jackson-Silah DJ, Adegbola RA, et al. Identifying ELISPOT and skin test cut-offs for diagnosis of Mycobacterium tuberculosis infection in The Gambia. Int J Tuberc Lung Dis. 2006;10(2):192-8. (Non Commercial Assay)

45. Kang YA, Lee HW, Yoon HI, Cho B, Han SK, Shim YS, et al. Discrepancy between the tuberculin skin test and the whole-blood interferon gamma assay for the diagnosis of latent tuberculosis infection in an intermediate tuberculosis-burden country. JAMA. 2005 Jun 8;293(22):2756-61. (High-income country setting)

46. Kik SV, Franken WP, Mensen M, Cobelens FG, Kamphorst M, Arend SM, et al. Predictive value for progression to tuberculosis by IGRA and TST in immigrant contacts. Eur Respir J. 2009 Oct 19. (High-income country setting)

47. Kik SV, Franken WPJ, Arend SM, Mensen M, Cobelens FGJ, Kamphorst M, et al. Interferon-gamma release assays in immigrant contacts and effect of remote exposure to Mycobacterium tuberculosis. The International Journal of Tuberculosis and Lung Disease. 2009;13:820-8. (High-income country setting)

48. Kipfer B, Reichmuth M, Buchler M, Meisels C, Bodmer T. Tuberculosis in a Swiss army training camp: contact investigation using an Interferon gamma release assay. Swiss Med Wkly. 2008 May 3;138(17-18):267-72. (High-income country setting)

49. Kirkpatrick A, Bell C, Petrovic M, Woodhead M, Barrett A, Duffell E, et al. Investigation of a tuberculosis cluster at a job centre in Manchester, United Kingdom. Euro Surveill. 2006;11(11):273-5. (High-income country setting)

50. Kobashi Y, Obase Y, Fukuda M, Yoshida K, Miyashita N, Fujii M, et al. Usefulness of QuantiFERON TB-2G, a diagnostic method for latent tuberculosis infection, in a contact investigation of health care workers. Internal medicine (Tokyo, Japan). 2007;46(18):1543-9. (High-income country setting)

51. Lalvani A, Pathan AA, Durkan H, Wilkinson KA, Whelan A, Deeks JJ, et al. Enhanced contact tracing and spatial tracking of Mycobacterium tuberculosis infection by enumeration of antigen-specific T cells. Lancet. 2001 Jun 23;357(9273):2017-21. (High-income country setting)

52. Lee SH, Lew WJ, Kim HJ, Lee HK, Lee YM, Cho CH, et al. Serial interferon-gamma release assays after rifampicin prophylaxis in a tuberculosis outbreak. Respir Med. Mar;104(3):448-53. (High-income country setting)

53. Lew WJ, Jung YJ, Song JW, Jang YM, Kim HJ, Oh YM, et al. Combined use of QuantiFERON-TB Gold assay and chest computed tomography in a tuberculosis outbreak. The International Journal of Tuberculosis and Lung Disease. 2009;13:633-9. (High-income country setting)

54. Lewinsohn DA, Zalwango S, Stein CM, Mayanja-Kizza H, Okwera A, Boom WH, et al. Whole blood interferon-gamma responses to mycobacterium tuberculosis antigens in young household contacts of persons with tuberculosis in Uganda. PLoS ONE. 2008;3(10):e3407. (Non Commercial Assay)

55. Lienhardt C, Fielding K, Hane AA, Niang A, Ndao CT, Karam F, et al. Evaluation of the prognostic value of IFN-gamma release assay and tuberculin skin test in household contacts of infectious tuberculosis cases in Senegal. PLoS ONE.5(5):e10508. (Non Commercial Assay)

56. Lighter J, Rigaud M, Eduardo R, Peng CH, Pollack H. Latent tuberculosis diagnosis in children by using the QuantiFERON-TB Gold In-Tube test. Pediatrics. 2009 Jan;123(1):30-7. (High-income country setting)

57. Mantegani P, Piana F, Codecasa L, Galli L, Scarpellini P, Lazzarin A, et al. Comparison of an In-house and a Commercial RD1-based ELISPOT-IFN-{gamma} Assay for the Diagnosis of Mycobacterium tuberculosis Infection. Clin Med Res. 2006 Dec;4(4):266-72. (High-income country setting)

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58. Molicotti P, Bua A, Mela G, Olmeo P, Delogu R, Ortu S, et al. Performance of QuantiFERON-TB testing in a tuberculosis outbreak at a primary school. The Journal of pediatrics. 2008 Apr;152(4):585-6. (High-income country setting)

59. Mutsvangwa J, Millington KA, Chaka K, Mavhudzi T, Cheung YB, Mason PR, et al. Identifying recent Mycobacterium tuberculosis transmission in the setting of high HIV and TB burden. Thorax. Apr;65(4):315-20. (Non Commercial Assay)

60. Nienhaus A, Schablon A, Bacle CL, Siano B, Diel R. Evaluation of the interferon-gamma release assay in healthcare workers. International archives of occupational and environmental health. 2008 Jan;81(3):295-300. (High-income country setting)

61. Ohno H, Ikegami Y, Kishida K, Yamamoto Y, Ikeda N, Taniguchi T, et al. A contact investigation of the transmission of Mycobacterium tuberculosis from a nurse working in a newborn nursery and maternity ward. J Infect Chemother. 2008 Feb;14(1):66-71. (High-income country setting)

62. O'Neal S, Hedberg K, Markum A, Schafer S. Discordant tuberculin skin and interferon-gamma tests during contact investigations: a dilemma for tuberculosis controllers. Int J Tuberc Lung Dis. 2009 May;13(5):662-4. (High-income country setting)

63. Pathan AA, Wilkinson KA, Klenerman P, McShane H, Davidson RN, Pasvol G, et al. Direct ex vivo analysis of antigen-specific IFN-gamma-secreting CD4 T cells in Mycobacterium tuberculosis-infected individuals: associations with clinical disease state and effect of treatment. J Immunol. 2001 Nov 1;167(9):5217-25. (High-income country setting)

64. Piana F, Codecasa LR, Cavallerio P, Ferrarese M, Migliori GB, Barbarano L, et al. Use of a T-cell-based test for detection of tuberculosis infection among immunocompromised patients. Eur Respir J. 2006 Jul;28(1):31-4. (High-income country setting)

65. Piana F, Ruffo Codecasa L, Baldan R, Miotto P, Ferrarese M, Cirillo DM. Use of T-SPOT.TB in latent tuberculosis infection diagnosis in general and immunosuppressed populations. New Microbiol. 2007 Jul;30(3):286-90. (High-income country setting)

66. Richeldi L, Bergamini BM, Vaienti F. Prior tuberculin skin testing does not boost QuantiFERON-TB results in paediatric contacts. Eur Respir J. 2008 Aug;32(2):524-5. (High-income country setting)

67. Richeldi L, Ewer K, Losi M, Bergamini BM, Roversi P, Deeks J, et al. T cell-based tracking of multidrug resistant tuberculosis infection after brief exposure. Am J Respir Crit Care Med. 2004 Aug 1;170(3):288-95. (High-income country setting)

68. Richeldi L, Ewer K, Losi M, Roversi P, Fabbri LM, Lalvani A. Repeated tuberculin testing does not induce false positive ELISPOT results. Thorax. 2006 Feb;61(2):180. (High-income country setting)

69. Ringshausen FC, Schlosser S, Nienhaus A, Schablon A, Schultze-Werninghaus G, Rohde G. In-hospital contact investigation among health care workers after exposure to smear-negative tuberculosis. J Occup Med Toxicol. 2009 Jun 8;4(1):11. (High-income country setting)

70. Shams H, Weis SE, Klucar P, Lalvani A, Moonan PK, Pogoda JM, et al. Enzyme-Linked Immunospot and Tuberculin Skin Testing to Detect Latent Tuberculosis Infection. Am J Respir Crit Care Med. 2005 Aug 4. (High-income country setting)

71. Silverman MS, Reynolds D, Kavsak PA, Garay J, Daly A, Davis I. Use of an interferon-gamma based assay to assess bladder cancer patients treated with intravesical BCG and exposed to tuberculosis. Clin Biochem. 2007 Apr 27. (High-income country setting)

164

72. Soborg B, Koch A, Thomsen VO, Ladefoged K, Andersson M, Wohlfahrt J, et al. Ongoing tuberculosis transmission to children in Greenland. Eur Respir J. Jun 1. (High-income country setting)

73. Soysal A, Millington KA, Bakir M, Dosanjh D, Aslan Y, Deeks JJ, et al. Effect of BCG vaccination on risk of Mycobacterium tuberculosis infection in children with household tuberculosis contact: a prospective community-based study. Lancet. 2005 Oct 22-28;366(9495):1443-51. (Non Commercial Assay)

74. Storla DG, Kristiansen I, Oftung F, Korsvold GE, Gaupset M, Gran G, et al. Use of interferon gamma-based assay to diagnose tuberculosis infection in health care workers after short term exposure. BMC Infect Dis. 2009;9:60. (High-income country setting)

75. Taggart EW, Hill HR, Ruegner RG, Litwin CM. Evaluation of an in vitro assay for interferon gamma production in response to the Mycobacterium tuberculosis-synthesized peptide antigens ESAT-6 and CFP-10 and the PPD skin test. American journal of clinical pathology. 2006 Mar;125(3):467-73. (High-income country setting)

76. Taggart EW, Hill HR, Ruegner RG, Martins TB, Litwin CM. Evaluation of an in vitro assay for gamma interferon production in response to Mycobacterium tuberculosis infections. Clinical and diagnostic laboratory immunology. 2004 Nov;11(6):1089-93. (High-income country setting)

77. Taylor RE, Cant AJ, Clark JE. Potential effect of NICE tuberculosis guidelines on paediatric tuberculosis screening. Archives of disease in childhood. 2008 Mar;93(3):200-3. (High-income country setting)

78. Tuuminen T, Sorva S, Liippo K, Vasankari T, Soini H, Eriksen-Neuman B, et al. Feasibility of commercial interferon-gamma-based methods for the diagnosis of latent Mycobacterium tuberculosis infection in Finland, a country of low incidence and high bacille Calmette-Guerin vaccination coverage. Clin Microbiol Infect. 2007 May 14. (High-income country setting)

79. Vekemans J, Lienhardt C, Sillah JS, Wheeler JG, Lahai GP, Doherty MT, et al. Tuberculosis contacts but not patients have higher gamma interferon responses to ESAT-6 than do community controls in The Gambia. Infect Immun. 2001 Oct;69(10):6554-7. (Non Commercial Assay)

80. Whalen CC, Chiunda A, Zalwango S, Nshuti L, Jones-Lopez E, Okwera A, et al. Immune correlates of acute Mycobacterium tuberculosis infection in household contacts in Kampala, Uganda. The American journal of tropical medicine and hygiene. 2006 Jul;75(1):55-61. (Non Commercial Assay)

81. Winthrop KL, Nyendak M, Calvet H, Oh P, Lo M, Swarbrick G, et al. Interferon-{gamma} Release Assays for Diagnosing Mycobacterium tuberculosis Infection in Renal Dialysis Patients. Clin J Am Soc Nephrol. 2008 Jun 11. (High-income country setting)

82. Yoshiyama T, Harada N, Higuchi K, Sekiya Y, Uchimura K. Use of the QuantiFERON-TB Gold test for screening tuberculosis contacts and predicting active disease. Int J Tuberc Lung Dis. Jul;14(7):819-27. (High-income country setting)

83. Zellweger JP, Zellweger A, Ansermet S, de Senarclens B, Wrighton-Smith P. Contact tracing using a new T-cell-based test: better correlation with tuberculosis exposure than the tuberculin skin test. Int J Tuberc Lung Dis. 2005 Nov;9(11):1242-7. (High-income country setting)

165

Annex 8. Selection of studies evaluating the predictive value of IGRAs for incident active TB disease in low, middle and high income countries

Total identified published records

that met search criteria up to

31May2010

(n = 724)

Scre

enin

g In

clu

ded

El

igib

ility

Id

enti

fica

tio

n

Additional records identified

through other sources

(n = 3 )

Abstracts and Reports Retrieved for

Screening

Records screened

(n = 727 )

Records excluded

(n = 708 )

Full-text articles assessed

for eligibility

(n = 19 )

Full-text articles excluded

(n = 7 )

Studies included in

qualitative synthesis

(n = 12 )

Studies included in quantitative synthesis (meta-analysis)

(n = 6 and 7, for estimation of rates and incidence rate ratios, respectively)

(n=12, for cumulative incidence risk ratios)

166

Included studies

1. Bakir M, Millington KA, Soysal A, Deeks JJ, Efee S, Aslan Y, et al. Prognostic value of a T-cell-based, interferon-gamma biomarker in children with tuberculosis contact. Ann Intern Med. 2008; 149(11): 777-87.

2. Doherty TM, Demissie A, Olobo J, Wolday D, Britton S, Eguale T, et al. Immune responses to the Mycobacterium tuberculosis-specific antigen ESAT-6 signal subclinical infection among contacts of tuberculosis patients. J Clin Microbiol. 2002; 40(2): 704-6.

3. Diel R, Loddenkemper R, Meywald-Walter K, Niemann S, Nienhaus A. Predictive value of a whole blood IFN-gamma assay for the development of active tuberculosis disease after recent infection with Mycobacterium tuberculosis. Am J Respir Crit Care Med. 2008; 177(10): 1164-70.

4. Aichelburg MC, Rieger A, Breitenecker F, Pfistershammer K, Tittes J, Eltz S, et al. Detection and prediction of active tuberculosis disease by a whole-blood interferon-gamma release assay in HIV-1-infected individuals. Clin Infect Dis. 2009; 48(7): 954-62.

5. Kik SV, Franken WP, Mensen M, Cobelens FG, Kamphorst M, Arend SM, et al. Predictive value for progression to tuberculosis by IGRA and TST in immigrant contacts. Eur Respir J. 2009; 35(6): 1346-53.

6. del Corral H, Paris SC, Marin ND, Marin DM, Lopez L, Henao HM, et al. IFNgamma response to Mycobacterium tuberculosis, risk of infection and disease in household contacts of tuberculosis patients in Colombia. PLoS One. 2009; 4(12): e8257.

7. Yoshiyama T HN, Higuchi K, Sekiya Y, Uchimura K. Use of the QuantiFERON TB Gold Test for screening tuberculosis contacts and predicting active disease. Int J Tuberc Lung Dis. 2010; 14(7).

8. Lienhardt C, Fielding K, Hane AA, Niang A, Ndao CT, Karam F, et al. Evaluation of the prognostic value of IFN-gamma release assay and tuberculin skin test in household contacts of infectious tuberculosis cases in Senegal. PLoS One. 2010; 5(5): e10508.

9. Leung C. C YWC, Yew W.W, Ho P.L, Tam C.K, Law W.S, Au K.F, Tsui P.W. T-Spot.TB outperforms tuberculin skin test in predicting tuberculosis disease. AJRCCM. 2010; In Press.

10. Shanaube K HJ, Hensen B, Beyers N, Ayles H, Godfrey-Faussett P. QuantiFERON in ZAMSTAR Report: Summary of baseline data: ZAMSTART; 2010.

11. Mahomed H. Predictive value of baseline TST and QFT in an adolescent cohort in a high-burden setting in South Africa: SATVI; 2010.

12. Hill PC, Brookes RH, Fox A, Jackson-Sillah D, Jeffries DJ, Lugos MD, et al. Longitudinal assessment of an ELISPOT test for Mycobacterium tuberculosis infection. PLoS Med. 2007; 4(6): e192.


1. Clark SA, Martin SL, Pozniak A, Steel A, Ward B, et al. (2007) Tuberculosis antigen-specific immune responses can be detected using enzyme-linked immunospot technology in human immunodeficiency virus (HIV)-1 patients with advanced disease. Clin Exp Immunol 150: 238-244. (Predictive value of IGRA was not a primary objective, furthermore, a mixture of patients that included those who were on TB treatment already, those who were TB suspects, and ‘healthy’ patients was followed-up; the risk of subsequent TB was not stratified by the various sub-groups (prevalent and incident cases were combined).

2. Elliott AM, Hodsdon WS, Kyosiimire J, Quigley MA, Nakiyingi JS, et al. (2004) Cytokine responses and progression to active tuberculosis in HIV-1-infected Ugandans: a prospective study. Trans R Soc Trop Med Hyg 98: 660-670. (RD1 antigens were not used)

3. Elliott JH, Vohith K, Saramony S, Savuth C, Dara C, et al. (2009) Immunopathogenesis and diagnosis of tuberculosis and tuberculosis-associated immune reconstitution inflammatory syndrome during early antiretroviral therapy. J Infect Dis 200: 1736-1745. (Predictive value of IGRA was not a primary objective)

167

4. Haldar P (2009) Contact screening with single-step TIGRA testing and risk of active TB infection: The Leicester Cohort. Thorax. (Conference Abstract) (Study identified only in abstract form, but could not be included because of insufficient information)

5. Higuchi K, Harada N, Mori T, Sekiya Y (2007) Use of QuantiFERON-TB Gold to investigate tuberculosis contacts in a high school. Respirology 12: 88-92. (Older QuantiFEROn technology was evaluated)

6. Higuchi K, Kondo S, Wada M, Hayashi S, Ootsuka G, et al. (2009) Contact investigation in a primary school using a whole blood interferon-gamma assay. J Infect 58: 352-357. (Older QuantiFEROn technology was evaluated)

7. Ordway DJ, Costa L, Martins M, Silveira H, Amaral L, et al. (2004) Increased Interleukin-4 production by CD8 and gammadelta T cells in health-care workers is associated with the subsequent development of active tuberculosis. J Infect Dis 190: 756-766. (RD1 antigens were not used)

use of interferon-γ release assays (igras) in tuberculosis control … · and igra positivity...

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