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HbA1c in the diagnosis of type 2 diabetes: a systematic review
Introduction
The use of HbA1c for diagnosis of type 2 diabetes is not currently recommended by
the World Health Organization (WHO) (WHO 2006). The reasons cited in the 2006
report included that HbA1c measurement was not widely available in many countries
throughout the world, global consistency in its measurement was problematic, and
that the HbA1c result is influenced by several factors including anaemia and
abnormalities of haemoglobin.
There is now renewed interest in HbA1c as a diagnostic criterion for diabetes.
Consequently this systematic review was undertaken to address this question.
Research Question
How does HbA1c perform in the diagnosis of type 2 diabetes based on the detection
and prediction of microvascular complications?
Methods
OBJECTIVE
To review best available evidence on the performance of HbA1c for the diagnosis of
diabetes, based on the detection and prediction of microvascular complications.
CRITERIA FOR CONSIDERING STUDIES FOR THIS REVIEW
Type of study
Cohort studies evaluating the association between HbA1c levels and prevalent or
incident microvascular complications.
Case-report, case-control and case-series studies and letters or commentaries were
excluded.
Type of participants Adults aged 18 years and older with or without diabetes.
Types of outcome measures
The following outcomes were included:
Main outcome
• HbA1c cut-point associated with prevalent or incident microvascular
complications associated with diabetes (e.g. retinopathy, microalbuminuria)
• Acceptable forms of analyzing data on this association including sensitivity and
specificity, ROC curve analysis, change point analysis, inspection of
decile/vigintile distribution, and inspection of continuous plots.
• Preference was given to studies using the most recent WHO diagnostic criteria,
however studies using older WHO or ADA diagnostic criteria were also included.
Other outcomes
2
• FPG and 2-h PG cut-points associated with prevalent or incident microvascular
complications (e.g. retinopathy, microalbuminuria)
• Sensitivity and specificity, ROC curve analysis, change point analysis, inspection
of decile/vigintile distribution, and inspection of continuous plots describing the
association between HbA1c, FPG or 2-h PG values and prevalent or incident
microvascular complications
Search methods for identification of studies
Electronic searches Databases were searched for relevant articles published between January 1990 and
September 2010. The January 1990 start date was selected because HbA1c
measurement was first developed in the late 70’s, did not become routinely used in
clinical practice until the late 80’s and the first reports relevant to this review were
published in the mid-90’s.
The following databases were searched:
• Medline
• Embase
• Pubmed
• Cinahl
• Psycinfo
• The Cochrane Library
A separate search strategy, specific for each electronic database was used for each
search. These searches can be found in Appendix 1.
Searching was carried out using a combination of keywords that cover all relevant
terminology for type 2 diabetes and the MESH terms HbA1c, type 2 diabetes,
diagnosis and complications. These searches were supplemented by reviewing
reference lists of relevant articles.
The relevance of articles was determined according to the inclusion and exclusion
criteria.
• Inclusion criteria require that the articles were conducted in humans (aged ≥ 18
years), contained cohorts with prevalent or incident cases of undiagnosed or
newly diagnosed type 2 diabetes, with diagnosis of diabetes based on the oral
glucose tolerance test (OGTT) or fasting plasma glucose (FPG) (using WHO
2006 or other established criteria); published in any language.
• Exclusion criteria were letters, commentaries, time series, case reviews or case-
control studies; all included participants had known diabetes.
METHODS OF THE REVIEW
Data Collection and analysis The inclusion of studies was assessed independently by two assessors. Articles were
only rejected on the initial screen if:
• the reviewer could determine from the title and abstract that the article was a time
series or case review or case-control study or letter or commentary;
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• the study did not include measured HbA1c values
• the study did not report prevalent or incident microvascular complications
When a title/abstract could not be rejected with certainty, the full text of the article
was obtained for further evaluation.
Data abstraction was performed independently. Differences between reviewer’s
results were resolved by discussion and reanalysis of studies and by returning to the
relevant literature. A third reviewer was available to resolve any disagreement.
Assessing Study Quality and Level of Evidence Methodological quality of each study was assessed according to the Australian
National Health and Medical Research Council (NHMRC) criteria for assessing study
quality and grading the level of evidence (Appendix 2).
Quality assessment was not used as an exclusion criterion.
The GRADE (Grading of Recommendations Assessment, Development and
Evaluation) program was also used to generate summary of findings tables
(Schunemann et al. 2008).
Results The search strategy identified 9680 studies. The majority of these were found to be
irrelevant upon reading the title, requiring only 134 abstracts to be read. Of these, 11
met the inclusion criteria and were included in the review. A summary of reviewed
studies is detailed below and is summarised in the attached Tables.
HbA1c and the detection of prevalent microvascular complications McCance and colleagues (1994) performed a cross-sectional analysis of FPG, 2h
plasma glucose (PG) and HbA1c and the presence of microvascular complications
(retinopathy and nephropathy) associated with type 2 diabetes in Pima Indians aged
≥25 years (n=960) who were not receiving insulin or oral hypoglycaemic treatment at
baseline. The cut-points which achieved maximum sensitivity and specificity for
detecting retinopathy were ≥ 7.2 mmol/L for FPG (sensitivity 81%, specificity 80%),
≥ 13.0 mmol/L for 2h PG (sensitivity 88%, specificity 81%), and ≥ 7.0% for HbA1c
(sensitivity 78%, specificity 85%). Cut-points that were equivalent to the WHO 2h
PG criterion of ≥ 11.1 mmol/L (sensitivity 88%, specificity 76%) for detecting
retinopathy were ≥ 6.8 mmol/L for FPG (sensitivity 81%, specificity 77%) and ≥
6.1% for HbA1c (sensitivity 81%, specificity 77%). The prevalence of type 2 diabetes
detected using the optimal cut-points for FPG was 22%, 2 h PG 21% and for HbA1c
17%. The areas under the curve for nephropathy were not as good as those for
retinopathy.
Engelgau et al. (1997) performed a cross-sectional study of 1,018 Egyptians aged ≥
20 years to compare FPG, 2h PG and HbA1c for diagnosing type 2 diabetes and to
evaluate the performance of the WHO 1980 criteria. Of this population, 27% had
known diabetes (91% of whom were receiving antihyperglycaemic medication) and
8% had undiagnosed diabetes. Cut-points for each glycaemic measure were calculated
for OGTT defined diabetes as 1) the upper component of the fitted bimodal
distribution for each glycaemic measure, and 2) the presence of diabetic retinopathy.
4
The point of intersection of the lower and upper components that minimised
misclassification were ≥ 7.2 mmol/L for FPG, ≥ 11.5 mmol/L for 2h PG, and ≥ 6.7%
for HbA1c. The sensitivities for FPG, 2h PG and HbA1c were 84%, 90%, and 68%,
respectively; the specificities were all 100%. The prevalence of retinopathy increased
above the sixth decile for FPG values (median glucose 6.6 mmol/L in seventh decile)
and above the seventh decile for 2h PG (median glucose 14.4 mmol/L in eight decile)
and HbA1c (median HbA1c 7.6% in eight decile) values. When diabetic retinopathy
was used to define type 2 diabetes in the entire population, area under the receiver
operator characteristic curve (AROC) analysis revealed that both FPG (0.85) and 2h
PG (0.86) were superior to HbA1c (0.82; p < 0.01). In the total population, the
sensitivity and specificity for detecting diabetic retinopathy were approximately equal
for FPG, 2h PG and HbA1c cut-points of ≥ 7.8 mmol/l, ≥ 12.8 mmol/L, and ≥ 6.9%,
respectively.
In an analysis of NHANES III data on 2,821 individuals aged 40-74 years in whom
FPG, 2h PG and HbA1c were measured, all three measurements were strongly
associated with retinopathy (The Expert Committee on the Diagnosis and
Classification of Diabetes Mellitus 1997). The prevalence of type 2 diabetes increased
in the highest decile of each variable, corresponding to FPG ≥ 6.7 mmol/L, 2h PG ≥
10.8 mmol/L, and HbA1c ≥ 6.2%.
Miyazaki and colleagues (2004) compared FPG, 2h PG and HbA1c to diagnose type 2
diabetes based on the prevalence of retinopathy in a Japanese population of 1,637
subjects aged 40-79 years from the Hisayama study. Of these subjects, 2.3% had
diabetic retinopathy. All three measures were strongly associated with retinopathy.
The prevalence of retinopathy dramatically increased in the tenth decile of each
variable, corresponding to an FPG of ≥ 6.5 mmol/L, a 2h PG ≥ 11.0 mmol/L, and an
HbA1c of ≥ 5.8%. The prevalence of retinopathy in the tenth decile of FPG, 2h PG
and HbA1c was 16%, 20% and 20%, respectively. According to AROC analysis, the
optimal cut-points for the diagnosis of diabetes were 6.4 mmol/L for FPG, 11.1
mmol/L for 2h PG, and 5.7% for HbA1c. At these cut-points the three measurements
has identical sensitivity (87%) and similar specificity (87%-90%) for detecting type 2
diabetes. The AROC curve for detecting type 2 diabetes was not significantly
different between any of the three measurements (FPG 0.96, 2h PG 0.90, and HbA1c
0.95).
The association of FPG, 2h PG and HbA1c with retinopathy and microalbuminuria
was assessed by Tapp et al. (2006). Data were obtained from 2,182 participants with
retinal photographs and 2,389 with urinary albumin/creatinine results from the
AusDiab study (subjects aged ≥ 25 years). The prevalence of retinopathy in the first
eight deciles of FPG and HbA1c and the first nine deciles of 2 h PG was 7.2, 6.6, and
6.3%, respectively, showing no variation with increasing glucose or HbA1c (subjects
with known diabetes were excluded from these analyses). Above these levels, the
prevalence of retinopathy rose sharply to 18.6, 21.3, and 10.9%, respectively. The
thresholds for increased prevalence of retinopathy were ≥ 7.1 mmol/L for FPG, ≥ 6.1%
for HbA1c, and ≥ 13.1 mmol/L for 2h PG. The prevalence of microalbuminuria rose
more gradually across the deciles for each glycaemic measure. The thresholds were
less clear than for retinopathy, but were found at ≥ 7.2 mmol/L for FPG and ≥ 6.1%
for HbA1c, with no evidence of a threshold for 2h PG. For FPG the adjusted threshold
for retinopathy using a change point model was 8.5 mmol/L (95%CI 6.4-10.6%, p =
5
0.008) and for HbA1c ≥ 6.0% (95% CI 3.9-7.0%, p = 0.064). The association of 2h
PG and retinopathy was not assessed due to limited numbers, and there was no
significant thresholds observed for any measure of glycaemia with microalbuminuria
using change point models.
Ito and colleagues (2000a) evaluated FPG, 2h PG and HbA1c for the diagnosis of
diabetes based on the prevalence of retinopathy. The subjects were 12,208 Japanese
atomic-bomb survivors who underwent an OGTT between 1965 and 1997 (mean age
at initial test 59 years). The prevalence of retinopathy increased sharply and
significantly above the eighth decile with FPG (≥ 7.0 mmol/L), above the seventh
decile for 2h PG (≥ 11.0 mmol/L) and above the ninth decile of HbA1c (≥ 7.3%).
Wong and colleagues (2008) assessed data from three cross-sectional studies to
examine the relationship between FPG and retinopathy for the diagnosis of diabetes.
The three cohorts included 3,162 Australian subjects aged 45-97 years from the Blue
Mountains Eye Study (BMES), 2,182 Australian subjects aged 25-90 years from the
Australian Diabetes, Obesity and Lifestyle Study (AusDiab) and 6,079 US subjects
aged 45-84 years from the Multi-Ethnic Study of Atherosclerosis (MESA). The
prevalence of retinopathy was 11.5% in BMES, 9.6% in AusDiab and 15.8% in
MESA. Results indicate inconsistent evidence for a uniform glycaemic threshold for
retinopathy, with the suggestion of a continuous relationship. Across the three
cohorts, a FPG cut-point of ≥ 7.0 mmol/L had a low sensitivity ranging from 15-39%
for detecting retinopathy, with specificity between 81-96%. The AROC for FPG in
detecting retinopathy was low and ranged from 0.56 to 0.61. In a separate analysis,
the relationship between 2h PG and prevalent retinopathy was assessed in the
AusDiab cohort. A 2 hour plasma glucose cut-point of ≥ 11.1 mmol/L performed
worse than FPG in identifying prevalent retinopathy in this population, with a
sensitivity of 25%, specificity of 81% and AROC of 0.54. The authors also reported a
continuous relationship between prevalent retinopathy and glycated haemoglobin in
the MESA cohort, with change point models showing no evidence of a glycaemic
threshold.
The DETECT-2 collaboration conducted an analysis to determine whether there is a
glycaemic threshold for diabetic retinopathy (Colagiuri et al. Diabetes Care in press).
Three glycaemic measures, FPG, 2h PG and HbA1c, were examined. The analysis
included 12 studies from nine countries with a total of 47,364 participants aged 20-79
years with gradable retinal photographs. The prevalence of any retinopathy in people
with known diabetes was 23.1%, newly diagnosed diabetes 5.4%, impaired glucose
tolerance (IGT) 2.8%, impaired fasting glucose (IFG) 4.3% and normal glucose
tolerance (NGT) 4.0%. Based on visual inspection of vigintile distribution, there was
a glycaemic threshold for diabetes-specific retinopathy (moderate or more severe
retinopathy), at 6.4-6.8 mmol/L for FPG, 9.8-10.6 mmol/L for 2h PG and 6.4-6.8%
for HbA1c. When change point analyses with glycaemic measures plotted as the
continuous variable were used, no threshold was found for any measure of glycaemia
for diabetes-specific retinopathy. Based on ROC analyses, the optimal cut-points for
detecting diabetes-specific retinopathy in all subjects were 6.5 mmol/L for FPG, 12.4
mmol/L for 2 h PG and 6.3% for HbA1c. At these cut-points the AROCs, sensitivities
and specificities were 0.87, 82% and 81% for FPG; 0.89, 83% and 83% for 2h PG;
and 0.90, 86% and 86% for HbA1c.
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HbA1c and incident microvascular complications A recent study by Massin and colleagues (in press, Archives of Ophthalmology)
compared the predictive values of baseline HbA1c and FPG for the development of
retinopathy over 10 years in 700 French subjects (aged 30-65 years at entry) from the
DESIR study. Of the study population, 235 had diabetes (treatment of FPG ≥ 7.0
mmol/L at least once over the preceding nine years), 238 always had NGT, and 227
had IFG at least once. The 44 subjects with retinopathy at 10 years had higher
baseline mean HbA1c (6.4 ± 1.6% vs. 5.7 ± 0.7%) and FPG (7.2 ± 2.7 mmol/L vs. 5.9
± 1.2 mmol/L) than those without retinopathy (both p < 0.0001). The 10-year
prevalence of retinopathy was 3.6% in the entire population and 16% for those with
HbA1c ≥ 6.5% and FPG ≥ 6.5 mmol/L. The 10-year prevalence of retinopathy was
3.3% for HbA1c < 6.0% and 6.8% for those with a higher HbA1c. An HbA1c of 6.0%
had a positive predictive value (PPV) of 6.8%, a negative predictive value (NPV) of
97%, a sensitivity of 16%, a specificity of 97%, and a positive likelihood ratio (PLR)
of 2.0 for 10-year retinopathy. For an HbA1c of 6.5%, these values were 15.9%, 97%,
7.9%, 97% and 2.4. For an FPG of 6.0 mmol/L these values were 8.6%, 97%, 27%,
90% and 2.6, while for a FPG of 6.5 mmol/L they were 17.4%, 97%, 21%, 96% and
5.7. A threshold above which retinopathy increased could not be determined from
these results due the small sample size and low frequency of 10-year retinopathy.
Van Leiden and colleagues (2003) evaluated the effect of HbA1c, among other risk
factors, on the incidence of retinopathy in 233 people aged 50-74 years with normal
and abnormal glucose metabolism from the Hoorn Study. Average follow-up was 9.4
years (range 7.9-11.0 years). The cumulative incidences of retinopathy among those
with normal, impaired, and diabetic glucose metabolism were 7.3%, 13.6%, and
17.5%, respectively. The cumulative incidence increased from 6.0% for those in the
lowest tertile of HbA1c to 20.7% for those in the highest tertile (p = 0.005 for trend).
The crude odds ratio for retinopathy were 2.01 and 2.71 for individuals with impaired
glucose metabolism and those with type 2 diabetes, respectively, compared with
individuals with normal glucose metabolism. The adjusted odds ratio for retinopathy
was 3.29 (95%CI 1.11-9.72) for the highest tertile of HbA1c at baseline. Limiting this
analysis to those without type 2 diabetes, the adjusted odds ratio for retinopathy in the
highest tertile of baseline HbA1c was 3.54 (0.94-13.37). Baseline HbA1c was
significantly higher in those who developed retinopathy at follow-up (6.1 ± 1.0%)
compared with those who did not (5.6 ± 1.0%, p = 0.03).
Prospective data were also reported by the McCance et al. (1994) on the development
to microvascular complications. However, as the data involved a combination of
measurement of HbA1 and measurement of HbA1c, it was considered inappropriate
for inclusion in this review.
7
Summary
1. The major objective of diagnosing diabetes is to prevent premature mortality and
complication-related morbidity. Therefore it seems logical to consider diagnosis in
terms of risk of complications.
2. Diagnostic criteria would ideally be derived from a study of outcomes and
complications in an untreated prospective cohort measuring different potential
diagnostic criteria at baseline. Alternatively outcomes could be compared with
different diagnostic criteria in intervention studies. A sub-group analysis of the
ADDITION study might have the power to examine this.
3. In the absence of the above information, the relationship of complications
(diabetes-specific) with direct or indirect measures of glucose can be examined,
either prospectively or in cross-sectional analysis.
4. Most of the data of the relationship of measures of glycaemia and retinopathy are
derived from cross-sectional studies. HbA1c levels associated with retinopathy
ranged from 5.8-7.3%. The DETECT-2 analysis pooled data from 47,364 people
and reported an HbA1c of approximately 6.5% as the threshold for diabetes-
specific retinopathy.
5. The DESIR study examined FPG and HbA1c and 10-year incident retinopathy. A
threshold above which retinopathy increased could not be determined due to small
sample and low frequency of 10-year retinopathy. An HbA1c of 6.5% had a PPV
of 15.9%, NPV of 97%, sensitivity of 7.9%, and specificity of 97%.
Acknowledgements
Funding for the systematic review was provided by the World Health Organization.
8
References
Colagiuri, S., C. M. Y. Lee, T. Y. Wong, B. Balkau, J. Shaw and K. Borch-Johnsen
(In press, Diabetes Care). "Is there a glycemic threshold for diabetic
retinopathy?".
Engelgau, M. M., T. J. Thompson, W. H. Herman, J. P. Boyle, R. E. Aubert, S. J.
Kenny, A. Badran, E. S. Sous and M. A. Ali (1997). "Comparison of fasting
and 2-hour glucose and HbA1c levels for diagnosing diabetes. Diagnostic
criteria and performance revisited." Diabetes Care 20(5): 785-791.
Ito, C., R. Maeda, S. Ishida, H. Harada, N. Inoue and H. Sasaki (2000a). "Importance
of OGTT for diagnosing diabetes mellitus based on prevalence and incidence
of retinopathy." Diabetes Res Clin Pract 49(2-3): 181-186.
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Balkau (In press, Archives of Ophthalmology). "HbA1c and fasting plasma
glucose as predictors of retinopathy at ten years: the French D.E.S.I.R. Study."
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Bennett and W. C. Knowler (1994). "Comparison of tests for glycated
haemoglobin and fasting and two hour plasma glucose concentrations as
diagnostic methods for diabetes." BMJ 308(6940): 1323-1328.
Miyazaki, M., M. Kubo, Y. Kiyohara, K. Okubo, H. Nakamura, K. Fujisawa, Y. Hata,
S. Tokunaga, M. Iida, Y. Nose and T. Ishibashi (2004). "Comparison of
diagnostic methods for diabetes mellitus based on prevalence of retinopathy in
a Japanese population: the Hisayama Study." Diabetologia 47(8): 1411-1415.
Schunemann, H. J., A. D. Oxman, J. Brozek, P. Glasziou, R. Jaeschke, G. E. Vist, J.
W. Williams, Jr., R. Kunz, J. Craig, V. M. Montori, P. Bossuyt and G. H.
Guyatt (2008). "Grading quality of evidence and strength of recommendations
for diagnostic tests and strategies." BMJ 336(7653): 1106-1110.
Tapp, R. J., P. Z. Zimmet, C. A. Harper, M. P. de Courten, D. J. McCarty, B. Balkau,
H. R. Taylor, T. A. Welborn and J. E. Shaw (2006). "Diagnostic thresholds for
diabetes: the association of retinopathy and albuminuria with glycaemia."
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(1997). "Report of the Expert Committee on the Diagnosis and Classification
of Diabetes Mellitus." Diabetes Care 20(7): 1183-1197.
van Leiden, H. A., J. M. Dekker, A. C. Moll, G. Nijpels, R. J. Heine, L. M. Bouter, C.
D. Stehouwer and B. C. Polak (2003). "Risk factors for incident retinopathy in
a diabetic and nondiabetic population: the Hoorn study." Arch Ophthalmol
121(2): 245-251.
WHO (2006). Definition and diagnosis of diabetes mellitus and intermediate
hyperglycemia. Geneva, World Health Organization.
Wong, T. Y., G. Liew, R. J. Tapp, M. I. Schmidt, J. J. Wang, P. Mitchell, R. Klein, B.
E. Klein, P. Zimmet and J. Shaw (2008). "Relation between fasting glucose
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9
Table 1 HbA1c and prevalent microvascular complications – study characteristics
Author, year
and country
Subject no
and gender
(M/F)
Age
(years)
Prevalence of
diabetes (%)
Inclusion/ exclusion
criteria
HbA1c test method Glucose
method
Diabetes
diagnostic
criteria
Blood
sample
Colagiuri et
al. (in press,
Diabetes Care), International
47,364
22,127/
25,237
20-79 14.3 Age 20-79 years with
gradable retinal
photographs and data for at
least one measure of
glycaemia (FPG, 2h PG or
HbA1c)
Varies by study Varies by
study
WHO 1999 Varies by
study
Engelgau et
al. (1997),
Egypt
1,018
417/601
Mean:
45
35.6 ≥ 20 years old, Egyptian
(note: includes people with
known diabetes, many of
whom were receiving anti-
hyperglycaemic treatment)
Affinity chromatography
(Pierce Scientific)
CV: 6.0%
Glucose
oxidase
WHO 1980 Capillary
blood and
Serum
glucose
Expert
Committee
(1997), US
2,821
NR
40-74 NR NR NR NR NR NR
Ito et al.
(2000a),
Japan
12,208
6,440/5,768
58.6 ±
11.6
NR Japanese atomic bomb
survivors
HPLC Glucose
oxidase
WHO 1999 Venous
plasma
McCance et
al. (1994), US
– Pima Indian
960
384/576
≥ 25 14-26 depending
on measurement
and cut-point
(26.3 for 2-h PG ≥
11.1 mmol/L)
Pima Indian subjects ≥ 25
years of age not receiving
insulin or oral
hypoglycaemic treatment at
baseline
HPLC Potassium
ferricyanide
WHO 1985 Venous
plasma
Miyazaki et
al. (2004),
Japan
1,637 40-79 21-23 depending
on measurement
(21 for 2-h PG ≥
11.1 mmol/L)
Age 40-79 years, not
receiving insulin treatment
(note: includes people
receiving oral anti-
hyperglycaemic treatment)
HPLC Glucose
oxidase
WHO 1999 Venous
plasma
Tapp et al.
(2006),
Australia
2,476
1,114/1,362
Mean:
59
34.5 Age ≥ 25 years Boronate affinity HPLC
(Bio-Rad Variant
Haemoglobin Testing
System)
CV: < 2%
Olympus
AU600
analyser
WHO 1999 Venous
plasma
2-h PG = 2 hour plasma glucose; ADA = American Diabetes Association; BMI = body mass index; CV = coefficient of variation; HPLC = high-performance liquid
chromatography; NR = not reported; WHO = World Health Organization.
10
Table 2 HbA1c, FPG and 2-h PG cut-points associated with prevalent microvascular complications HbA1c FPG 2-h PG Study Complication
Optimum
cut-point
(%)
AROC Sensitivity
(%)
Specificity
(%)
Optimum
cut-point
(mmol/L)
AROC Sensitivity
(%)
Specificity
(%)
Optimum
cut-point
(mmol/L)
AROC Sensitivity
(%)
Specificity
(%)
Retinopathy
(ROC curve
analysis)
≥6.3 0.90 86 86 ≥6.5 0.87 82 81 ≥12.4 0.89 83 83
Colagiuri et
al. (in press, Diabetes Care)
Retinopathy
(visual inspection
of decile
distribution)
6.4-6.8 NR NR NR 6.4-6.8 NR NR NR 9.8-10.6 NR NR NR
Bi-modal:
- Entire
population
≥6.7
NR
68
100
≥7.2
NR
84
100
≥11.5
NR
90
100
Engelgau et
al. (1997)
Retinopathy#:
- Entire
population
≥7.6
0.82
NR
NR
≥6.6
0.85*
NR
NR
≥14.4
0.86*
NR
NR
Expert
Committee,
(1997)
Retinopathy
≥6.2 NR NR NR ≥6.7 NR NR NR ≥10.8 NR NR NR
Ito et al.
(2000a)
Retinopathy ≥7.3 NR NR NR ≥7.0 NR NR NR ≥11.0 NR NR NR
Retinopathy ≥7.0 NR 78 85 ≥7.2 NR 81 80 ≥13.0 NR 88 81
WHO equivalent ≥6.1 NR 81 77 ≥6.8 NR 81 77 ≥11.1 NR 88 76
McCance et
al. (1994)
ROC curve
analysis ≥5.7 0.95 87 90 ≥6.4 0.96 87 87 ≥11.1 0.90 87 90
Miyazaki et
al. (2004)
Retinopathy ≥5.8 NR NR NR ≥6.5 NR NR NR ≥11.0 NR NR NR
Retinopathy ≥6.1 NR NR NR ≥7.1 NR NR NR ≥13.1 NR NR NR
Microalbuminuria ≥6.1 NR NR NR ≥7.2 NR NR NR NR NR NR NR
Retinopathy§ ≥6.0 NR NR NR ≥8.5 NR NR NR NR NR NR NR
Tapp et al.
(2006)
Microalbuminuria NIL - - - NIL - - - NR NR NR NR
* Significantly different from HbA1c (p < 0.01); # Median decile value; § By change point analysis. 2-h PG = 2 hour plasma glucose; AROC = Area under the receiver
operator characteristic curve; FPG = fasting plasma glucose; NR = Not reported; ROC = receiver operator characteristic; WHO = World Health Organization.
11
Table 3 HbA1c and incident microvascular complications – study characteristics
Author,
year and
country
Subject no
and gender
(M/F)
Age
(years)
Follow-
up
(years)
Incidence of
diabetes (%)
Inclusion/ exclusion criteria HbA1c test method Glucose
method
Diabetes
diagnostic
criteria
Blood
sample
Massin et al.
(in press,
Archives of
Ophthalmol),
France
700
504/196
30-65 10 NR
Retinopathy:
6.3
Aged 30-65 years. Excluded if
uninterpretable retinal photographs
HPLC (Hitachi/Merck-
VWR) or
DCA 2000 automated
immunoassay system
(Bayer Diagnostics)
Glucose
oxidase
NR Venous
plasma
Van Leiden
et al. (2003),
Netherlands
233
124/109
50-74 9.4 NR
Retinopathy:
11.6
Aged 50-74 years from Hoorn,
Netherlands.
HPLC (Modular
Diabetes Monitoring
system; Bio-Rad)
Normal range: 4.3-6.1%
Glucose
dehydrogenase
WHO 1999 Venous
plasma
HPLC = high-performance liquid chromatography; NR = not reported; WHO = World Health Organization.
12
Table 4 HbA1c and FPG cut-points associated with incident diabetes complications
HbA1c FPG Study Complication
Optimum
cut-point
(%)
AROC Sensitivity
(%)
Specificity
(%)
Optimum
cut-point
(mmol/L)
AROC Sensitivity
(%)
Specificity
(%)
Massin et al.
(in press,
Archives of
Ophthalmol)
Retinopathy ≥ 6.0 NR 16 97 ≥ 6.5 NR 21 96
AROC = Area under the receiver operator characteristic curve; FPG = fasting plasma glucose; NR = Not reported.
13
Table 5. Evidence table for HbA1c and prevalent microvascular complications
Evidence Level of Evidence
Author (year),
population Level Study Type
Quality Rating Magnitude of
effect rating
Relevance
Rating
Colagiuri et al. (in press,
Diabetes Care),
International
N/A Pooled
Analysis High High High
Engelgau et al. (1997),
Egypt III-2 Cohort Medium High High
Expert Committee
(1997), US III-2 Cohort Medium Medium High
Ito et al. (2000a), Japan II Cohort High High High
McCance et al. (1994),
US – Pima Indian II Cohort High High High
Miyazaki et al. (2004),
Japan III-2 Cohort High High High
Tapp et al. (2006),
Australia III-2 Cohort High Medium High
Table 6. Evidence table for HbA1c and incident microvascular complications
Evidence Level of Evidence
Author (year),
population Level Study Type
Quality Rating Magnitude of
effect rating
Relevance
Rating
Massin et al. (in press,
Archives of Ophthalmology),
France
II Prospective
Cohort High Medium High
Van Leiden et al. (2003),
Netherlands II
Prospective
Cohort High Medium High
14
Table 7. GRADE table for HbA1c and detection of prevalent microvascular complications
Factors that may decrease quality of evidence
Outcome No. of
studies
Study
design Limitations Indirectness Inconsistency Imprecision Reporting bias
Final
quality Effect per 10001 Importance
True positives
(patients with prevalent complications)
3 studies2
(31,797 patients)
Observational None3 None None None Unlikely ⊕⊕⊕O
moderate
Prev 80%: 672
Prev 40%: 336 Prev 10%: 84
IMPORTANT
True negatives (patients
without prevalent
complications)
3
(31,797
patients)
Observational None3 None None None Unlikely ⊕⊕⊕O
moderate
Prev 80%: 172
Prev 40%: 516
Prev 10%: 774
IMPORTANT
False positives (patients
incorrectly classified as
having prevalent
complications)
3
(31,797
patients)
Observational None3 None None None Unlikely ⊕⊕⊕O
moderate
Prev 80%: 28
Prev 40%: 84
Prev 10%: 126
IMPORTANT
False negatives (patients
incorrectly classified as not having prevalent
complications)
3
(31,797
patients)
Observational None3 None None None Unlikely ⊕⊕⊕O
moderate
Prev 80%: 128
Prev 40%: 64
Prev 10%: 16
IMPORTANT
Inconclusive 4 4 studies (19,142
patients)
Observational – – – – – – – IMPORTANT
Cost Not reported – – – – – – – – NOT
RELEVANT
1 Based on combined sensitivity of 84% and specificity of 86%
2 One study contained pooled data from 8 studies with 29,819 participants
3 Although not a serious limitation, one study oversampled people with known diabetes
4 These 4 studies did not report information on sensitivity and specificity of HbA1c for predicting prevalent microvascular complications
15
Table 8. GRADE table for HbA1c and incident microvascular complications
Factors that may decrease quality of evidence
Outcome No. of
studies
Study
design Limitations Indirectness Inconsistency Imprecision Reporting bias
Final
quality Effect per 10002 Importance
True positives
(patients with incident complications)
1 study
(700 patients) Observational None None N/A2
Not
assessable3 Unlikely
⊕⊕OO
low
Prev 80%: 128
Prev 40%: 64 Prev 10%: 16
IMPORTANT
True negatives (patients
without incident
complications)
1
(700 patients) Observational None None N/A2
Not
assessable3 Unlikely
⊕⊕OO
low
Prev 80%: 194
Prev 40%: 582
Prev 10%: 873
IMPORTANT
False positives (patients
incorrectly classified as
having incident
complications)
1
(700 patients) Observational None None N/A2
Not
assessable3 Unlikely
⊕⊕OO
low
Prev 80%: 6
Prev 40%: 18
Prev 10%: 27
IMPORTANT
False negatives (patients
incorrectly classified as not having incident
complications)
1
(700 patients) Observational None None N/A2
Not
assessable3 Unlikely
⊕⊕OO
low
Prev 80%: 672
Prev 40%: 336
Prev 10%: 84
IMPORTANT
Inconclusive 4
1 study (233 patients)
Observational – – – – – – – IMPORTANT
Cost Not reported – – – – – – – – NOT
RELEVANT
2 Based on combined sensitivity of 16% and specificity of 97%
2 Imprecision could not be assessed as confidence intervals were not reported
3 Inconsistency is not applicable with data from only one study 4 This study did not report information on sensitivity and specificity of HbA1c for predicting incident microvascular complications
16
Appendix 1
Search for HbA1c in the diagnosis of diabetes (search covers both sections: incident and
prevalent complications associated with HbA1c)
Search 1: Database: Ovid MEDLINE
Search Strategy:
--------------------------------------------------------------------------------
1 Diabetes Mellitus, Type 2/ (62685)
2 (type 2 diabetes or type II diabetes).tw. (42266)
3 (non?insulin dependent diabetes or NIDDM).tw. (7555)
4 1 or 2 or 3 (75337)
5 Hemoglobin A, Glycosylated/ (16909)
6 hba1c.tw. (8615)
7 h?emoglobin A1c.tw. (3166)
8 Glyco?h?emoglobin.tw. (653)
9 Glycated h?emoglobin.tw. (2802)
10 Glycosylated h?emoglobin.tw. (5302)
11 5 or 6 or 7 or 8 or 9 or 10 (24975)
12 Diagnosis/ (15662)
13 Diagnostic Tests, Routine/ (5441)
14 diagnos$.tw. (1271525)
15 exp Diabetes Complications/ (87841)
16 complication$.tw. (456183)
17 retinopath$.tw. (23219)
18 12 or 13 or 14 or 15 or 16 or 17 (1733665)
19 4 and 11 and 18 (4191)
20 limit 19 to (humans and yr="1990 - 2010") (3973)
***************************
17
Search 2 – Embase
No. Query Results
#22 #4 AND #12 AND #21 AND [humans]/lim AND [1990-
2010]/py 4132
#21 #13 OR #14 OR #15 OR #16 OR #17 OR #18 OR #19 OR
#20 2677720
#20 'retinopathy':ab,ti OR 'retinopathies':ab,ti 28677
#19 'complication':ab,ti OR 'complications':ab,ti 569736
#18 'diabetic retinopathy'/de 22102
#17 'diagnosis':ab,ti OR 'diagnostic':ab,ti OR 'diagnosed':ab,ti OR
'diagnoses':ab,ti 1545712
#16 'laboratory diagnosis'/de 35794
#15 'diagnostic procedure'/de 60017
#14 'diagnostic test'/de 46436
#13 'diagnosis'/de 805045
#12 #5 OR #6 OR #7 OR #8 OR #9 OR #10 OR #11 36114
#11 'glycosylated hemoglobin'/de 10917
#10 'glycosylated haemoglobin':ab,ti OR 'glycosylated
hemoglobin':ab,ti 6271
#9 'glycated haemoglobin':ab,ti OR 'glycated hemoglobin':ab,ti 3457
#8 'glycohaemoglobin':ab,ti OR 'glycohemoglobin':ab,ti 801
#7 'haemoglobin a1c':ab,ti OR 'hemoglobin a1c':ab,ti 2600
#6 hba1c:ab,ti 8781
#5 'hemoglobin a1c'/de 21712
#4 #1 OR #2 OR #3 103193
#3 'non insulin dependent diabetes':ab,ti OR 'noninsulin
dependent diabetes':ab,ti OR 'niddm':ab,ti 13423
#2 'type 2 diabetes':ab,ti OR 'type ii diabetes':ab,ti 55623
#1 'non insulin dependent diabetes mellitus'/de 87826
18
Search 3 – Pubmed
Search History
Search Queries Result
#18 Search #4 AND #10 AND #17 Limits: Humans, Publication Date from 1990 to 2010 7191
#17 Search #11 or #12 or #13 or #14 or #15 or #16 6064084
#16 Search retinopath*[Title/Abstract] 23768
#15 Search complication*[Title/Abstract] 474432
#14 Search diabetes complications[MeSH Terms] 86714
#13 Search diagnos*[Title/Abstract] 1320078
#12 Search diagnostic tests, routine[MeSH Terms] 5308
#11 Search diagnosis[MeSH Terms] 5190551
#10 Search #5 or #6 or #7 or #8 or #9 24308
#9 Search glycosylated haemoglobin or glycosylated hemoglobin[Title/Abstract] 18889
#8 Search glycated haemoglobin or glycated hemoglobin[Title/Abstract] 17668
#7 Search glycohaemoglobin or glycohemoglobin[Title/Abstract] 670
#6 Search hba1c[Title/Abstract] 9034
#5 Search hba1c[MeSH Terms] 16240
#4 Search #1 or #2 or #3 87454
#3 Search non?insulin dependent diabetes or niddm[Title/Abstract] 76711
#2 Search type 2 diabetes or type II diabetes[Title/Abstract] 75342
#1 Search type 2 diabetes[MeSH Terms] 60587
19
Search 4 – Cinahl
# Query Limiters/Expanders Results
S20 S4 and S11 and S18
Limiters - Published Date
from: 19900101-20101231;
Human
Search modes -
Boolean/Phrase
512
S19 S4 and S11 and S18 Search modes -
Boolean/Phrase 703
S18 S12 or S13 or S14 or S15 or S16 or S17 Search modes -
Boolean/Phrase 148780
S17 TI retinopath* or AB retinopath* Search modes -
Boolean/Phrase 1585
S16 TI complication* or AB complication* Search modes -
Boolean/Phrase 38685
S15 TI diagnos* or AB diagnos* Search modes -
Boolean/Phrase 109484
S14 (MH "Diagnosis, Laboratory") Search modes -
Boolean/Phrase 6119
S13 (MH "Diagnostic Tests, Routine") Search modes -
Boolean/Phrase 783
S12 (MH "Diagnosis") Search modes -
Boolean/Phrase 2056
S11 S5 or S6 or S7 or S8 or S9 or S10 Search modes -
Boolean/Phrase 5717
S10 TI ( glycosylated haemoglobin or glycosylated hemoglobin ) or
AB ( glycosylated haemoglobin or glycosylated hemoglobin )
Search modes -
Boolean/Phrase 837
S9 TI ( glycated haemoglobin or glycated hemoglobin ) or AB (
glycated haemoglobin or glycated hemoglobin )
Search modes -
Boolean/Phrase 390
20
S8 TI ( glycohaemoglobin or glycohemoglobin ) or AB (
glycohaemoglobin or glycohemoglobin )
Search modes -
Boolean/Phrase 66
S7 TI ( (haemoglobin a1c or hemoglobin a1c) ) or AB (
(haemoglobin a1c or hemoglobin a1c) )
Search modes -
Boolean/Phrase 816
S6 TI hba1c or AB hba1c Search modes -
Boolean/Phrase 2208
S5 (MH "Hemoglobin A, Glycosylated") Search modes -
Boolean/Phrase 3908
S4 S1 or S2 or S3 Search modes -
Boolean/Phrase 18051
S3
TI ( (non insulin dependent diabetes or noninsulin dependent
diabetes or non-insulin dependent diabetes or niddm) ) or AB (
(non insulin dependent diabetes or noninsulin dependent
diabetes or non-insulin dependent diabetes or niddm) )
Search modes -
Boolean/Phrase 839
S2 TI ( (type 2 diabetes or type II diabetes) ) or AB ( (type 2
diabetes or type II diabetes) )
Search modes -
Boolean/Phrase 10448
S1 (MH "Diabetes Mellitus, Non-Insulin-Dependent") Search modes -
Boolean/Phrase 15554
21
Search 5 – Psycinfo
Database: PsycINFO
Search Strategy:
--------------------------------------------------------------------------------
1 (type 2 diabetes or type II diabetes).tw. (2117)
2 (non?insulin dependent diabetes or NIDDM).tw. (148)
3 1 or 2 (2248)
4 hba1c.tw. (493)
5 h?emoglobin A1c.tw. (199)
6 Glyco?h?emoglobin.tw. (19)
7 Glycated h?emoglobin.tw. (102)
8 Glycosylated h?emoglobin.tw. (311)
9 4 or 5 or 6 or 7 or 8 (883)
10 diagnosis/ (24273)
11 diagnos$.tw. (177767)
12 "Complications (Disorders)"/ (756)
13 complication$.tw. (11553)
14 retinopath$.tw. (379)
15 10 or 11 or 12 or 13 or 14 (189699)
16 3 and 9 and 15 (106)
17 limit 16 to (human and yr="1990 - 2010") (104)
***************************
22
Search 6 – Cochrane Library Current Search
ID Search Hits
#1 MeSH descriptor Diabetes Mellitus, Type 2 explode all trees 6415
#2 (type 2 diabetes or type II diabetes):ti,ab,kw 8982
#3 (non insulin dependent diabetes or non insulin dependent diabetes or non-insulin dependent diabetes or niddm):ti,ab,kw
2020
#4 (#1 OR #2 OR #3) 9548
#5 MeSH descriptor Hemoglobin A, Glycosylated, this term only 2656
#6 (hba1c):ti,ab,kw 1642
#7 (haemoglobin a1c or hemoglobin a1c):ti,ab,kw 788
#8 (glycohaemoglobin or glycohemoglobin):ti,ab,kw 69
#9 (glycated haemoglobin or glycated hemoglobin):ti,ab,kw 476
#10 (glycosylated haemoglobin or glycosylated hemoglobin):ti,ab,kw 3168
#11 (#5 OR #6 OR #7 OR #8 OR #9 OR #10) 4352
#12 MeSH descriptor Diagnosis, this term only 65
#13 MeSH descriptor Diagnostic Tests, Routine, this term only 293
#14 (diagnos*):ti,ab,kw 66662
#15 MeSH descriptor Diabetes Complications explode all trees 3896
#16 (complication*):ti,ab,kw 71382
#17 (retinopath*):ti,ab,kw 1861
#18 (#12 OR #13 OR #14 OR #15 OR #16 OR #17) 129125
#19 (#4 AND #11 AND #18), from 1990 to 2010 1141
23
Appendix 2
NHMRC Evidence Hierarchy: designations of ‘levels of evidence’ according to type of research question (NHMRC 2007)
Level Intervention Diagnostic accuracy Prognosis Aetiology Screening Intervention
I
A systematic review of level II
Studies
A systematic review of level
II studies
A systematic review of level
II studies
A systematic review of level
II studies
A systematic review of level II
studies
II A randomised controlled trial A study of test accuracy with: an independent, blinded comparison with a valid reference standard,
among consecutive persons with a defined clinical presentation
A prospective cohort study
A prospective cohort study A randomised controlled trial
III-1 A pseudorandomised controlled trial
(i.e. alternate allocation or some
other method)
A study of test accuracy with: an independent, blinded comparison with a valid reference standard,
among non-consecutive persons with a defined clinical presentation
All or none All or none A pseudorandomised
controlled trial
(i.e. alternate allocation or
some other method)
II-2 A comparative study with
concurrent controls:
▪ Non-randomised,
experimental trial
▪ Cohort study
▪ Case-control study
▪ Interrupted time series with a
control group
A comparison with reference
standard that does not meet
the criteria required for
Level II and III-1 evidence
Analysis of prognostic
factors amongst persons in
a single arm of a
randomised controlled trial
A retrospective cohort study A comparative study with
concurrent controls:
▪ Non-randomised,
experimental trial
▪ Cohort study
▪ Case-control study
III-3 A comparative study without
concurrent controls:
▪ Historical control study
▪ Two or more single arm
study ▪ Interrupted time series without a
parallel control group
Diagnostic case-control
study
A retrospective cohort study A case-control study A comparative study without
concurrent controls:
▪ Historical control study
▪ Two or more single arm
study
IV Case series with either post-test
or pre-test/post-test outcomes Study of diagnostic
yield (no reference
standard)
Case series, or cohort study of
persons at different stages of
disease
A cross-sectional study or
case series
Case series
(Source: NHMRC 2007)
24
Study Assessment Criteria
I. Study quality criteria
Systematic reviews 1. Were the questions and methods clearly stated?
2. Is the search procedure sufficiently rigorous to identify all relevant studies?
3. Does the review include all the potential benefits and harms of the
intervention?
4. Does the review only include randomised controlled trials?
5. Was the methodological quality of primary studies assessed?
6. Are the data summarised to give a point estimate of effect and confidence
intervals?
7. Were differences in individual study results adequately explained?
8. Is there an examination of which study population characteristics (disease
subtypes, age/sex groups) determine the magnitude of effect of the
intervention?
9. Were the reviewers' conclusions supported by data cited?
10. Were sources of heterogeneity explored?
Randomised controlled trials 1. Were the setting and study subjects clearly described?
2. Is the method of allocation to intervention and control groups/sites
independent of the decision to enter the individual or group in the study ?
3. Was allocation to study groups adequately concealed from subjects,
investigators and recruiters including blind assessment of outcome?
4. Are outcomes measured in a standard, valid and reliable way?
5. Are outcomes measured in the same way for both intervention and control
groups?
6. Were all clinically relevant outcomes reported?
7. Are factors other than the intervention e.g. confounding factors, comparable
between intervention and control groups and if not comparable, are they
adjusted for in the analysis?
8. Were >80% of subjects who entered the study accounted for at its
conclusion?%
9. Is the analysis by intention to intervene (treat)?
10. Were both statistical and clinical significance considered?
11. Are results homogeneous between sites? (Multi-centre/multi-site studies only).
Cohort studies 1. Are study participants well-defined in terms of time, place and person?
2. What percentage (%) of individuals or clusters refused to participate?
3. Are outcomes measured in a standard, valid and reliable way?
4. Are outcomes measured in the same way for both intervention and control
groups?
5. Was outcome assessment blind to exposure status?
6. Are confounding factors, comparable between the groups and if not
comparable, are they adjusted for in the analysis?
7. Were >80% of subjects entered accounted for in results and clinical status
described?
25
8. Was follow-up long enough for the outcome to occur
9. Was follow-up complete and were there exclusions from the analysis?
10. Are results homogeneous between sites? (Multicentre/multisite studies only).
Case-control studies 1. Was the definition of cases adequate?
2. Were the controls randomly selected from the source of population of the
cases?
3. Were the non-response rates and reasons for non-response the same in both
groups?
4. Is possible that over-matching has occurred in that cases and controls were
matched on factors related to exposure?
5. Was ascertainment of exposure to the factor of interest blinded to case/control
status?
6. Is exposure to the factor of interest measured in the same way for both case
and control groups in a standard, valid and reliable way (avoidance of recall
bias)?
7. Are outcomes measured in a standard, valid and reliable way for both case and
control groups?
8. Are the two groups comparable on demographic characteristics and important
potential confounders? and if not comparable, are they adjusted for in the
analysis?
9. Were all selected subjects included in the analysis?
10. Was the appropriate statistical analysis used (matched or unmatched)?
11. Are results homogeneous between sites? (Multicentre/multisite studies only).
Diagnostic accuracy studies 1. Has selection bias been minimised
2. Were patients selected consecutively?
3. Was follow-up for final outcomes adequate?
4. Is the decision to perform the reference standard independent of the test results
(ie avoidance of verification bias)?
5. If not, what per cent were not verified?
6. Has measurement bias been minimised?
7. Was there a valid reference standard?
8. Are the test and reference standards measured independently (ie blind to each
other)
9. Are tests measured independently of other clinical and test information?
10. If tests are being compared, have they been assessed independently (blind to
each other) in the same patients or done in randomly allocated patients?
11. Has confounding been avoided?
12. If the reference standard is a later event that the test aims to predict, is any
intervention decision blind to the test result?
(Sources: adapted from NHMRC1999, NHMRC 2000a, NHMRC 2000b, Liddle et al
96; Khan et al 2001)
26
Study quality – Rating The following was used to rate the quality of each study against the study type criteria
listed above.
High: all or all but one of the criteria were met
Medium: 2 or 3 of the criteria were not met
Low: 4 or more of the criteria were not met
27
II. Classifying magnitude of the effect
Ranking Statistical significance Clinical importance of
benefit
High Difference is statistically
significant
AND There is a clinically
important benefit for the
full range of estimates
defined by the confidence
interval.
Medium Difference is statistically
significant
AND The point estimate of effect
is clinically important
BUT the confidence
interval includes some
clinically unimportant
effects
Low Difference is statistically
significant|
OR
Difference is not statistically
significant (no effect) or
shows a harmful effect
AND
AND
The confidence interval
does not include any
clinically important effects
The range of estimates
defined by the confidence
interval includes clinically
important effects. (Source: adapted from the NHMRC classification (NHMRC 2000b)
III. Classifying the relevance of the evidence
Ranking Relevance of the evidence
High Evidence of an effect on patient-relevant clinical outcomes,
including benefits and harms, and quality of life and survival
Or
Evidence of an effect on a surrogate outcome that has been shown
to be predictive of patient-relevant outcomes for the same
intervention
Medium
Evidence of an effect on proven surrogate outcomes but for a
different intervention
Or
Evidence of an effect on proven surrogate outcomes but for a
different intervention and population
Low
Evidence confined to unproven surrogate outcomes.
(Source: adapted from the NHMRC classification (NHMRC 2000b)