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A Methodological Review of Models Used to Estimate the Cost-Effectiveness of Antiretroviral Regimens for the Treatment of HIV Infection Supplementary Material

Journal: Pharmacoeconomics

Author: Josephine Mauskopf, PhD

Corresponding Author: Josephine MauskopfRTI Health SolutionsE-mail: [email protected]

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ContentsTable 1. Markov Cohort Models in Discrete or Continuous Time: Detailed Review...3

Table 2. Monte Carlo Simulation Models: Detailed Review.....................................14

Table 3. Discrete Event Simulation or Continuous Time Markov Models: Detailed Review.......................................................................................................18

Table 4. Other Models: Detailed Review.................................................................21

Table 5. Economic Models for HIV Treatment: Number of Articles Found in Literature Search, January 11, 2013..........................................................................22

Table 6. PubMed Search Strategy...........................................................................22

Table 7. Embase Search Strategy...........................................................................24

Table 8. Cochrane Library Search Strategy............................................................25

References...............................................................................................................27

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Table 1. Markov Cohort Models in Discrete or Continuous Time: Detailed Review

Author, Year, Country

Health States/Cycle Time Other Model Structure Assumptions Uncertainty Analyses Validation

Simpson et al. (1994) [1]

Six CD4 cell count ranges (< 50, 50-99, 100-149, 150-199, 200-299, ≥ 300) and deathCycle time 2 months

Treatment changed pattern of CD4 cell count change over 1-year period only; OI risk by CD4 cell count; if OI, assigned life expectancy; if no OI after 12 months, assigned life expectancy

One-way sensitivity analysis for risk of OI, starting distribution of CD4 cell counts, life expectancy, future costs

None

Chancellor et al. (1997) [2]

Three HIV disease states: (CD4 > 200 and < 500 and non-AIDS, CD4 < 200 and non-AIDS, AIDS and death)Cycle time 1 year

Treatment reduced risk of transition between health states; 1- and 2-year and continuous effect tested

One-way sensitivity analysis for relative risk of progression, duration of effect, starting cohort CD4 cell counts, costs, and discount rates

None

Mauskopf et al. (1998) [3]

Five CD4 cell count ranges (< 100, 100-199, 200-349, 350-500, > 500) and deathCycle time 1 year

Treatment stops CD4 cell count decrease for 6.5 vs. 18 months, then progression at natural history rate

One-way sensitivity analysis for discount rates, duration of efficacy, post-trial efficacy treatment duration

Compared model results for first year to 1-year trial results

3



Biddle et al. (2000) [4]

Year 1 model: six CD4 cell count ranges (< 50, 50-99, 100-149, 150-199, 200-299, ≥ 300) and deathCycle time 2 months

Long-term model: four HIV disease states (CD4 ≥ 500; CD4 > 200 and < 500 and non-AIDS; CD4 < 200 and non-AIDS; AIDS) and deathCycle time 1 year

Year 1 model: treatment changed pattern of CD4 cell count change over 1-year period only; OI risk by CD4 cell count Long-term model: first-line treatment increased CD4 cell count with one-time transition to higher CD4 cell count health state; median time to return to baseline CD4 cell count was used to modify transition rates between health states; median time to virologic breakthrough and switch was 24 months longer for triple therapy than dual therapy. Second-line therapy with PIs, increase of 100 CD4 cells for 18 months; third-line PI, only 90% had CD4 cell count increase for 15 months

One-way sensitivity analysis for CD4 cell count at which treatment is started, duration of effect, and discount rates

None; but some validation of input parameters from published studies for durability of regimens including either nevirapine or PIs

4




Twelve combinations of CD4 cell count and viral load (CD4 > 500 + VL < 400 or ≥ 400; CD4 351-500 + VL < 400 or ≥ 400; CD4 201-350 + VL < 400, 400-19,999, or ≥ 20,000; CD4 50-200 + VL < 400, 400-19,999, 20,000-100,000, or > 100,000; CD4 < 50 + VL any level) and death3-month cycle time

First-line treatment efficacy allows progress into better or worse health states or health state remains unchanged; after 12 months, assume no further divergence in survival curve; switch to second line when CD4 < 500 and VL ≥ 400; switch to third line when CD4 < 350 and VL ≥ 400; health state improves on switch for 3 months (CD4 cell count increase and viral load decrease) then changes at the rates observed in two large observational database studies of people from their third quarter of HAART to the end of the study; overall OI rates varied by health state but relative frequency of OIs assumed the same for all health states; for this study only a sensitivity analysis was run that allowed differential efficacy for the second-line regimen based on resistance patterns after first-line

One-way sensitivity analysis for costs, utility weights and OI event rates, and discount rates

Model validated in separate publication though validation of OI rates from second observational database

Hornberger et al. (2005) [6]

Four HIV-related stages: start treatment no virologic failure (VF), VF, immunologic failure (IF) defined as return of CD4 cell count to baseline level, AIDS, and deathMonthly cycle time

Virologic failure defined as viral load never suppressed or rebound after suppression; rates of VF for first 12 months as in the trial; rates of VF after 12 months based on trial 3- to 12-month failure rates; CD4 cell count increases based on trial data for those without VF; between VF and IF, rate of decline of CD4 cell count depends on amount of viral suppression attained during therapy; after IF, rate of CD4 cell count decline equal to untreated rate; patients allowed to re-optimize OBR after VF but no efficacy assumed

One-way sensitivity analyses for treatment effectiveness, relevant progression probabilities, discount rates, medical care costs, time horizon and utilities

Stated that estimates for optimized background regimen for AIDS-free and survival are similar to those from observational studies in highly treatment-experienced individuals

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Hubben et al. (2007) [7]

See Simpson et al. (2004) [5]

See Simpson et al. (2004) [5]; but switch to second or third line when CD4 < 200 and VL ≥ 400

One-way sensitivity analysis for costs, disease progression rates, OI event rates, and discount rates



See Simpson et al. (2004) [5] but also including CHD, CHD death, and other death

See Simpson et al. (2004) [5]; but switch to second or third line when CD4 < 350 and VL ≥ 400; in addition, impact of ART on cholesterol levels and CHD risk using Framingham risk equations included

One-way and multi-way sensitivity analyses and scenario analyses with different impacts on cholesterol and different relationships between cholesterol and CHD


Simpson et al. (2007) [9, 10]

See Simpson et al. (2004) [5] but also including CHD, CHD death, and other death

See Simpson et al. (2004) [5]; but risk of viral rebound different for the different treatment regimens based on proportion with virologic suppression in the trial for the first-line regimen; switch to second or third line when CD4 < 350 and VL ≥ 400; in addition, impact of ART on cholesterol levels and CHD risk using Framingham risk equations included

One-way sensitivity analysis for duration of viral suppression, risk of heart disease, costs


Badia et al. (2007) [11]

Four HIV-related stages (start treatment and no virologic failure [VF], VF, IF, AIDS) and deathMonthly cycle time

See Hornberger et al. (2005) [6]CD4 cell count constant at the value in the last week of the clinical trial for those without VF and decreasing as a function of suppression of VL in last week of trial for those with VF or AIDS until IF, then at natural history rates

One-way sensitivity analyses for rate of virologic failure, relevant progression probabilities, discount rates, medical care costs, time horizon and base CD4 cell count and viral load

None

6





See Simpson et al. (2004) [5]; but switch to second or third line when CD4 < 200 and VL ≥ 400

One-way and probabilistic sensitivity analyses (PSA) based on cost of AIDS events, discount rate, utilities, switch drug costs, adverse event costs, and switch treatment efficacy; both Monte Carlo and bootstrap approaches for PSA


Simpson et al. (2009) [13, 14]

See Simpson et al. (2004) [5] but also including CHD, CHD death, AIDS event, and other death3-month cycle time

See Simpson et al. (2004) [5]; but switch to second or third line when CD4 < 350 and VL ≥ 400; in addition, impact of ART on cholesterol levels and CHD risk using Framingham risk equations included

One-way sensitivity analyses on cost of ritonavir boosting, cost of statins, cost of AIDS event, variation in prices of PIs for first regimen, effect of difference in baseline risk of CHD, cost of drugs used for second- and third-line treatment

Some comparison with CHD rates in the DAD observational cohort

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Elbasha et al. (2009) [15]

42 health states of combined CD4 cell count (> 500; 301-500; 201-300; 101-200; 51-100; 0-50) and viral load (> 100,000; 30,001-100,000; 10,001-30,000; 3,001-10,000; 401-3,000; 51-400; 0-50), also divided into those with and without history of OI; those with an OI enter temporary health states based on OI type (PCP, MAC, CMV, toxoplasmosis, fungal infections, other); continuous transitions modeled

Drug efficacy estimated using trial data for weeks 0 to 4 and 4 to 48 for movement through viral load states based on differential equations; CD4 cell count changes were estimated based on a regression equation relating viral load to CD4 cell count changes; virologic and immunologic failure rates were assumed to remain stable at the observed trial rates for 5 years, then 8% failure rate assumed while still on raltegravir; when raltegravir discontinued, rate of movement between states was set equal to the control group; no switch included, just remain on same OBR after discontinuing raltegravir; OI risk adjusted for impact of HAART; mortality from OIs, HIV-related, and general were included

One-way sensitivity analyses for utility weights, risk of OIs, price of raltegravir, duration of treatment with raltegravir, mortality rates, efficacy duration and treatment failure rates; variability analyses for analytic time horizon and discount rate

Model results compared to data from trials, cohort studies, and ART intervention studies including annual rate of death and outcomes of OIs

Chaudhary et al. (2009) [16]

See Elbasha et al. (2009) [15]

See Elbasha et al. (2009) [15] See Elbasha et al. (2009) [15]

See Elbasha et al. (2009) [15]; also life expectancy compared to that estimated in other models in treatment-experienced patients (life expectancy in this model is much longer than in other models)

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Moreno et al. (2010) [17]

Six CD4 cell count health states (> 500, 351-500, 201-350, 101-200, 51-100, 0-50) and death1-month cycle time with half-cycle correction

Transitions in first year taken from clinical trial; base-case duration of maraviroc therapy was 1 year only; after 1 year, both arms received OBR alone with virologic failure and CD4 cell count decline at the OBR rate for 6-12 months; after virologic failure, 1-month lag before CD4 cell count decline; CD4 cell count decline after AIDS taken from untreated cohort; AIDS-defining event estimated using observational data

One-way and probabilistic sensitivity analyses; one-way included treatment duration, model time horizon, rate of treatment success, lag time before CD4 cell count decline, transition probabilities between CD4 cell states, utilities, AIDS-defining event mortality rates, discount rates, and cost of maraviroc, OBT, enfuvirtide, HIV-related care, and AEs; 1,000 runs for PSA

None

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Six CD4 cell count health states (> 500, 351-500, 201-350, 101-200, 51-100, 0-50) plus death3-month cycle time

Efficacy via a rapid rise in CD4 cell count followed by a slower increase; rate of CD4 cell count increase (rapid and slow) and duration of slow increase varied by virologic response at 24 weeks (viral suppression, > 1 log10 drop but not suppressed, and < 1 log10 drop); switch to second OBR after treatment failure (defined as decline in CD4 cell count for at least 6 months) and continued for remaining lifetime; enfuvirtide therapy discontinued after 6-month period of decreasing CD4 cell count; after second regimen failed, declining CD4 cell count at a lower rate than untreated based on observational studies; HIV-related mortality rates related to CD4 cell count; non–HIV-related mortality related to age and was higher than general mortality rates by a factor

One-way and probabilistic sensitivity analyses; one-way analyses included extent and duration of treatment-induced increase in CD4 cell count for both initial treatment regimen and second-line treatment regimen; drug use, utility, costs, and HIV-related mortality; 1,000 runs for PSA; variability analyses for time horizon and discount rates

None

Moeremans et al. (2010) [19, 20]

See Mauskopf et al. (2010) [18]

See Mauskopf et al. (2010) [18] See Mauskopf et al. (2010) [18]

None

Brogan et al. (2010) [21]


See Mauskopf et al. (2010) [18] See Mauskopf et al. (2010) [18]

None

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Thuresson et al. (2011) [22]

Three health states for angina, myocardial infarction, stroke and death; also states for first-, second-, and third-line treatment; no health states for CD4 cell countCycle time ??

Treatment efficacy based on treatment discontinuations for any reason; after 96 weeks, discontinuation rate assumed equal for both regimens; subsequent treatment depended on reason for failure; CD4 cell count not tracked; adverse event incidence based on Framingham equation; costs for CV adverse events only; disutility from CVs from published studies and overall utility rate for HIV infection not varied by disease severity; second-line regimen depends on reach for discontinuation of first-line (adverse events, virologic failure, or compliance); efficacy of second- and third-line regimens from clinical trials with discontinuation rates resulting in switch to next line

One-way and PSA sensitivity analyses varying adverse events rates, treatment discontinuation rates, and cardiovascular profile

Validation against life expectancy in disease cohorts

Colombo et al. (2011) [23]

Eight health states from combinations of CD4 cell count and VL (CD4 > 500, VL < 50; CD4 > 500, VL > 50; CD4 350-500, VL < 50; CD4 350-500, VL > 50; CD4 200-350, VL < 50; CD4 200-350, VL > 50; CD4 < 200, VL < 50; CD4 > 200, VL > 50) plus AIDS and death Cycle time of 1 year and time horizon of 10 years

Efficacy measured by response to therapy and person placed in health states with viral load < 50; CD4 cell count allowed to move through states but no information provided on rates; response taken from trial data and assumed to stay constant at last observed value; treatment failures assigned to CD4 cell count states with VL > 50 and CD4 cell count assumed to decrease at untreated rates; with CD4 cell count < 200, transition to the AIDS state occurred; HIV-linked mortality related to CD4 cell count

One-way sensitivity analysis including virologic response, HIV-associated mortality rates, and initial distribution of patient CD4 cell counts and viral load

Compared average annual costs from the model with annual costs from an administrative database

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Brogan et al. (2011) [24]

Six CD4 cell count health states (> 500, 351-500, 201-350, 101-200, 51-100, ≤ 50) plus death1-year cycle period and lifetime horizon

Efficacy for first-line therapy measured using indirect comparison analysis for virologic response and CD4 cell count increase for the 144-week trial period; switch rate and CD4 cell count increase after trial period extrapolated from trial data; all patients switch to same second and subsequent therapy lines; duration on second- and third-line therapy taken from observational data; CD4 cell count increases based on clinical trials; no increase in CD4 cell count for salvage therapy; remain on salvage therapy for remaining lifetime; HIV-related mortality varied by CD4 cell count, while general mortality varied by age and sex with a 2.5-factor increase; adverse events for first-line therapy included in the model

One-way and probabilistic sensitivity analysis with realistic ranges for variables including efficacy of first-line therapy, annual changes in CD4 cell counts for later lines of therapy, and antiretroviral drug costs for later lines of therapy; variability analysis for model time horizon, discount rate, and incidence and cost of adverse events

Validated results with observational data on life expectancy for those with HIV infection initiating therapy and with percentage of deaths from HIV-related causes


See Simpson et al. (2004) [5]; in addition CHD, CHD death, AIDS event, and other death and lipoatrophy submodel3-month cycle time

See Simpson et al. (2004) [5]; but switch to second or third line when CD4 cell count < 350 and VL ≥ 400; resistance profile from first-line treatment assumed to increase the cost of third-line treatment by adding enfuvirtide; impact of ART on cholesterol levels and CHD risk using Framingham risk equations included; impact of ART on lipoatrophy with costs and disutility also included

One-way sensitivity analyses on impact of resistance on the cost of the third regimen and cost of AIDS, heart disease, or lipoatrophy and utility loss with lipoatrophy


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See Mauskopf et al. (2010) [18]; but switch regimen to include raltegravir plus OBR

See Mauskopf et al. (2010) [18]; variability analysis also included patient characteristics

One-year CD4 cell count distribution compared with that from the clinical trials used for efficacy estimates; proportion of HIV-related deaths compared with observed data in Canada; life expectancy compared with published estimates of life expectancy


See Simpson et al. (2004) [5]; in addition AIDS event, CHD, CHD death, and other death; 3-month cycle time

See Simpson et al. (2004) [5]; but switch to second or third line when CD4 cell count < 350 and VL ≥ 400; impact of ART on cholesterol levels and CHD risk using Framingham risk equations included

One-way sensitivity analysis for baseline risk of heart disease and costs of different lines of therapy only


AE = adverse events; AIDS = acquired immunodeficiency syndrome; ART = antiretroviral therapy; CD4 = CD4 T-lymphocyte or CD4 T-lymphocyte cell count; CHD = coronary heart disease; CMV = cytomegalovirus; CV = cardiovascular; DAD = Data Collection on Adverse events of Anti-HIV Drugs (observational cohort study); HAART = highly active antiretroviral therapy; HIV = human immunodeficiency virus; IF = immunologic failure; MAC = Mycobacterium avium complex; MI = myocardial infarction; OBR = optimized background regimen; OBT = optimized background therapy; OIs = opportunistic infections; PCP = Pneumocystis pneumonia; PI = protease inhibitor; PSA = probabilistic sensitivity analysis; VF = virologic failure; VL = viral load.

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Table 2. Monte Carlo Simulation Models: Detailed Review


Health Events/ Cycle Time Other Model Structure Assumptions Uncertainty Analysis Validation

Miners et al. (2001) [28]

Three HIV health events (CD4 ≥ 200 no AIDS, CD4 < 200 no AIDS, AIDS) plus death; 1-year cycle

Cohort of 1,000; treatment effects taken from observational data with different effects for first year and subsequent years of treatment; HAART effect mean of 5 years but costs of dual NRTI or HAART continued until death

One-way sensitivity analyses for additional cost of third drug, probability of disease progression, duration of cost for third drug, duration of HAART effect, model time horizon and discount rate

None

Freedberg et al. (2001) [29]CEPAC model

Chronic health events stratified by CD4 cell count (> 500, 301-500, 201-300, 101-200, 51-100, 0-50), viral load (> 30,000; 10,001-30,000; 3,001-10,000; 501-3000; ≤ 500), acute health state (with OIs) and history of clinical events plus death Initial 1-month cycle then 3-month cycle

Cohort of 1,000,000; efficacy represented by decrease in viral load, increase in CD4 cell count, reduced risk of opportunistic infections and AIDS-related death; no benefit of ART after 2 years; second-line regimen less effective than first-line regimen; impact of adherence or resistance modeled implicitly by adjusting efficacy rates; included long-term adverse events such as lipodystrophy as reduction in utility

One–way sensitivity analyses for duration of efficacy and toxicity of first-line therapy and costs and utility loss with lipodystrophy

None

Richter et al. (2002) [30]

Two health events defined by detectable viral load and AIDS stratified by six CD4 cell count categories (> 300, 201-300, 151-200, 101-150, 51-100, 0-50) and five viral load categories (< 500, 501-3000, 3001-10,000, 10,001-30,000, > 30,000) plus deathCycle time ?

Cohort size not specified; efficacy represented by probability of virologic suppression with increase in CD4 cell count in first cycle and then stable CD4 cell count; duration of efficacy was a random variable estimated by fitting a uniform distribution to trial data; efficacy for second-line therapy a fraction of that for first-line therapy; with treatment failure, viral load returns to set point; stops ART after failure of third-line regimen

One-way sensitivity analyses for probability of viral suppression, duration of suppression, and loss of efficacy with second-line therapy

Validation by comparing model with no ART and comparing results with natural history observational cohorts

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Sax et al. (2005) [31] CEPAC model

See Freedberg et al. [29]; death divided into HIV-related or other 1-month cycles

See Freedberg et al. [29]; instead of second-line therapy, OBR alone continued after failure of enfuvirtide + OBR

One–way sensitivity analyses for virologic and immunologic efficacy of initial therapy, reduction in OI risks with ART, OI history at baseline, and costs and utility loss with injection of enfuvirtide

Compared model survival and OI rates with OBR with natural history from observational studies; also compared to results from TORO trials

Kühne et al. (2010) [32]ARAMIS model

Chronic health states stratified by CD4 cell counts (> 500, 351-500, 201-350, 101-200, 51-100, 0-50) plus transition states (viral OI, bacterial OI, fungal OI, protozoal OI, other OI) plus death1-month cycles

Cohort of 200,000; risk of disease progression depends on OI history, CD4 cell count, and viral load; efficacy ; “set point viral load assigned randomly to each patient going through model; successful treatment drops viral load to < 400; CD4 cell count increases with viral suppression until late failure; adherence reflected implicitly in efficacy data; rapid CD4 cell count increase in first 2 months, then slower; after 48 weeks, CD4 cell count increase the same for both treatments; late failure rate treatment specific based on observed failure rate between 8 weeks and 48 weeks with a 10-year maximum durability”; all switched to same re-optimized background and stayed on this for their lifetime with reduced OI rate but after failure declining at the untreated rate; disutility for OIs and AEs

One-way sensitivity analyses based on patient resistance profile, maraviroc efficacy and durability, CCR5 prevalence and test cost, utility weights, replacement scenario, and alternative more effective re-OBT regimen

Indirect only, compared with the CEPAC model only

15



Contreras-Hernandez et al. (2010) [33]ARAMIS model

See Kühne et al. [32] See Kühne et al. [32] One-way and multiway sensitivity analyses based on OBT and maraviroc efficacy (virologic suppression and CD4 cell count increase) and durability, CCR5 prevalence and test cost, viral set point, and utility weights

Indirect, compared with the CEPAC model only

Broder et al. (2011) [34]

Chronic health states stratified by CD4 cell counts (> 350, 201-350, 50-200, < 50) plus events (AIDS diagnosis, CHD events, OI, diarrhea, hyperbilirubinemia) plus death3-month cycles

Cohort of 1,000,000; efficacy of treatment based on virologic suppression in trial; virologic failure rates beyond trial period based on trial period failure rates; CD4 cell count changes as observed in the clinical trial; adherence assumed to vary by treatment based on separate published studies; non-adherence increases risk of failure by 10%; all switched to the same second-line treatment with virologic failure or severe AEs; disutility for AEs and CHD events

One-way sensitivity analyses for initial treatment virologic response rates, TC:HDL ratios, adherence, utility weights for CHD events and diarrhea and hyperbilirubinemia; probabilistic sensitivity analysis varying all above parameters plus event rates for CHD, OIs and AEs, non-adherence rates, impact of nonadherence on HIV transitions and costs, utility weights for HIV states, non-drug medical costs by HIV state, and CHD and OI costs

None

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Walensky et al. (2013) [35]

See Freedberg et al. [29]1-month cycles

Cohort of 1,000,000; differential efficacy from poorer adherence to first-line therapy, lower efficacy of lamivudine than emtricitabine, and lower efficacy of second-line regimen because of increased risk of mutations on first-line regimen; virologic suppression rate at 24 weeks from two different trials and monthly late failure rates; adverse events rates, costs, and utility rates not included

One–way and multi-way sensitivity analyses for early virologic suppression rates and late failure rates, impact of mutation rates during first-line therapy on efficacy of second-line therapy, changes in starting CD4 cell counts, costs of ART, and risk group adjustments to non-HIV mortality

None

AE = adverse events; AIDS = acquired immunodeficiency syndrome; ART = antiretroviral therapy; ATV = atazanavir; CD4 = CD4 T-lymphocyte or CD4 T-lymphocyte cell count; CEPAC = Cost-Effectiveness of Preventing AIDS Complications (research team); CHD = coronary heart disease; HAART = highly active antiretroviral therapy; HDL = high-density lipoprotein (cholesterol); HIV = human immunodeficiency virus; ITT = intent to treat; LPV = lopinavir; NRTI = nucleoside reverse transcriptase inhibitors; OBR = optimized background regimen; OBT = optimized background therapy; OI = opportunistic infection; TC = total cholesterol.

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Table 3. Discrete Event Simulation or Continuous Time Markov Model: Detailed Review

Author, Year, Country Health Events

Other Model Structure Assumptions Uncertainty Analysis Validation


Initial characteristics—age, sex, CD4 cell count, viral load, ART naïve, CHD risk; clinical events change in viral load, change in CD4 cell count, utility weight, probability of AIDS-defining event, which AIDS-defining event and hospital LOS and death rate, probability of MI and hospital LOS and death rate, compliance with therapy; time step of 1 day

Event rates estimated from clinical trials and observational data studies; event rates vary within 4 time layers (first 8 weeks, 9 to 52 weeks, > 52-104 weeks and > 2 years); daily hazard rates estimated

None described One- and 5-year results of Markov model and DES model using similar data sources compared with observed results in trial cohort on one regimen followed for 5 years; DES model gave slightly better predictive validity

18



Aragão et al. (2012) [36]

Initial characteristics—age, sex, mode of transmission, employment status, HCV status, AIDS, HIV resistance level (inverted GSS < 1, 1-4, 5-9, 10-25), adherence level (changes with regimen characteristics), CD4 cell count, viral load, age of death due to non-HIV causes; clinical events viral suppression, regimen switch without viral failure (just one drug switch), line switch (assume viral failure), resistance development, hospitalization, AIDS-defining event or death; when event, occurs CD4 cell count, viral load, adherence level, resistance level, AIDS status, and regimen characteristics are updated

Cohort size 1,000,000; time to events and evolving patient state variables estimated using observational data and Weibull survival curves; line switches from first to second and second to third occurs if viral suppression is not reached within 12 months of line initiation or virologic failure (> 50) is confirmed; line switch from third line to nonsuppressive therapy occurs only when resistance reaches highest class; AE costs included

First-order from the simulation results; PSA using 50,000 individuals with 133 input combinations not specified taken from distributions using random draws; no one-way parameter sensitivity analyses or variability analyses

Extensive validation comparing outcomes with those from clinical trials (viral suppression rates) and observational data (changes in CD4 cell counts on successful therapy and on nonsuppressive therapy, rebound viral load after ART failure, number of regimen switches, life expectancy, time on first-line regimen)

19




Initial characteristics—age, sex, CD4 cell count, viral load, ART naïve, likelihood of adherence to treatment; propensity for having a resistance mutation at baseline, TC, HDL, triglycerides, smoker status, presence of diabetes mellitus, and systolic blood pressure; clinical events, AIDS-related events, acute and long-term AEs, time on initial and subsequent regimens, life expectancy, and QALYs

Virologic failure estimated from clinical trial for week 0 to 8 and then from week 8 to 96 adjusted down by relative rate of adherence compared with high adherence; late failure rates after 96 weeks estimated using linear regression of data for weeks 8 to 96; CD4 cell count changes modeled using trial data and assumed to continue; opportunistic infection rates tied to CD4 cell count; resistance pattern updated at virologic failure and influences subsequent treatment regimen; included 7 serious acute and 6 nonserious acute AEs and 4 long-term AEs; utility varied by CD4 cell count and disutility with ADEs and AEs

One-way and structural sensitivity analyses for adherence, baseline CD4 cell count, AIDS risk subgroup, CHD risk subgroup, females of child-bearing age; PSA varying unit costs and proportion in moderate adherence category; no sensitivity analyses on treatment efficacy

Model validity tested by simulating the results of a clinical trial

ADE = adverse drug events; AE = adverse events; AIDS = acquired immunodeficiency syndrome; ART = antiretroviral therapy; CD4 = CD4 T-lymphocyte or CD4 T-lymphocyte cell count; CHD = coronary heart disease; DES = discrete event simulation (model); GSS = genotypic sensitivity score; HCV = hepatitis C virus; HDL = high-density lipoprotein (cholesterol); HIV = human immunodeficiency virus; LOS = length of stay; MI = myocardial infarction; PSA = probabilistic sensitivity analysis; TC = total cholesterol.

20

Table 4. Other Models: Detailed Review

Author, Year, Country Health States


Schulman et al. (1991) [38]

Survival analysis to estimate time to AIDS

Efficacy just for 1 year or continues at the same rate after end of trial period; assumes life expectancy after conversion to AIDS is constant with and without treatment

One-way sensitivity analyses for magnitude of the survival benefit, cost of zidovudine, and lifetime costs associated with AIDS

None

Paltiel et al. (1991) [39]

Dynamic transmission model for HIV infection with events asymptomatic infected, asymptomatic not infected and AIDS; people also leaving the susceptible pool for other reasons

Efficacy increases the incubation time before conversion to AIDS;

Scenario analyses for different screening rates and time horizons

None

Anis et al. (2000) [40]

Survival function – to death Generated survival curves by estimating hazard rates for death relative to CD4 cell count, adjusting mortality rate for an untreated cohort after 1 year of treatment then assuming treatment effect decreased exponentially over time using observational data for three eras of ART; cost for drugs and OIs

One-, 2- and 3-way analyses for discounting, survival, costs, mortality rates, duration of treatment effect; also performed threshold analyses

None

Sánchez-de la Rosa et al. (2008) [41]

Events in decision tree are therapeutic success and failure over 24 months; also included 22 adverse events that occurred at a rate of > 1%

Data from 96-week trial used to estimate treatment success; included costs for AEs, drugs, and productivity loss; no costs associated with CD4 cell levels were included

One-way sensitivity analyses for drug prices, indirect costs, and discount rate

None

AE = adverse events; AIDS = acquired immunodeficiency syndrome; ART = antiretroviral therapy; CD4 = CD4 T-lymphocyte or CD4 T-lymphocyte cell count; HIV = human immunodeficiency virus; OIs = opportunistic infections.

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Table 5. Economic Models for HIV Treatment: Number of Articles Found in Literature Search, January 11, 2013

Database Records Unique RecordsPubMed 145 145Embase 147 73Cochrane Library 28 0Totals 320 218

Table 6. PubMed Search Strategy

Search Number Search Terms

Number of Articles

HIV/AIDS drug treatment#1 "HIV Infections/drug therapy"[Mesh] OR "Anti-HIV Agents"[Mesh] OR

"Antiretroviral Therapy, Highly Active"[Mesh] OR ("HIV Infections"[Mesh] AND ("Drug Therapy"[Mesh] OR "Drug Combinations"[Mesh:NoExp])) Filters: Publication date from 1990/01/01; English

61883

#2 ((reverse transcriptase inhibitor*[Title] OR NRTI*[Title] OR NNRTI*[Title] OR protease inhibitor*[Title] OR "PIs"[Title] OR fusion inhibitor*[Title] OR "FIs"[Title] OR integrase inhibitor*[Title] OR CCR5 antagonist*[Title] OR anti-retroviral*[Title] OR antiretroviral*[Title]) AND ("antiHIV"[Title] OR "anti-HIV"[Title] OR HIV*[Title] OR "AIDS"[Title]) AND drug*[Title]) OR (("antiHIV"[Title] OR "anti-HIV"[Title] OR HIV*[Title]) AND drug*[Title]) AND (treat*[Title] OR therap*[Title]) Filters: Publication date from 1990/01/01; English

1265

#3 (#1 OR #2) NOT ("HIV Infections/prevention and control"[Majr] OR prevent*[Title]) Filters: Publication date from 1990/01/01; English

57685

Geographic area#4 #3 NOT ("Africa"[Mesh] OR "Asia"[Mesh] OR "South America"[Mesh] OR

"Central America"[Mesh]) Filters: Publication date from 1990/01/01; English

51949

22


Number of Articles

Economic/decision models#5 #4 AND ("Economics, Pharmaceutical"[Mesh] OR "Drug Costs"[Mesh] OR

"Anti-HIV Agents/economics"[Mesh] OR "Antiretroviral Therapy, Highly Active/economics"[Mesh] OR "Drug Therapy/economics"[Mesh] OR "Costs and Cost Analysis"[Mesh] OR "Economics"[Mesh] OR "economics"[Subheading] OR pharmacoeconomic*[Text Word] OR cost*[Title] OR economic*[Title]) AND (evaluat*[Title] OR cost effective*[Title] OR "utility"[Title] OR "utilities"[Title] OR cost analy*[Title] OR cost consequence*[Title] OR "Decision Trees"[Mesh] OR "Markov Chains"[Mesh] OR decision analy*[Title] OR "Decision Support Techniques"[Mesh] OR decision tree*[Title] OR "Markov"[Title] OR simulation*[Title] OR "discrete"[Title] OR "Computer Simulation"[Mesh] OR decision*[Title]) AND ("Models, Economic"[Mesh] OR "Models, Statistical"[Mesh] OR model*[Text Word]) Filters: Publication date from 1990/01/01; English

133

Authors#6 #4 AND ("Economics, Pharmaceutical"[Mesh] OR "Drug Costs"[Mesh] OR

"Anti-HIV Agents/economics"[Mesh] OR "Antiretroviral Therapy, Highly Active/economics"[Mesh] OR "Drug Therapy/economics"[Mesh] OR "Costs and Cost Analysis"[Mesh] OR "Economics"[Mesh] OR "economics"[Subheading] OR pharmacoeconomic*[Text Word] OR cost*[Title] OR economic*[Title]) AND ("Models, Economic"[Mesh] OR "Models, Statistical"[Mesh] OR model*[Text Word]) AND ("Mauskopf"[Author] OR "Freedberg"[Author] OR "Paltiel"[Author] OR "Braithwaite"[Author] OR "Justice"[Author] OR "Sanders"[Author] OR "Simpson"[Author] OR "Roberts"[Author] OR "Hornberger"[Author] OR "Schackman"[Author] OR "Sax"[Author] OR "Weinstein"[Author] OR "Yazdanpanah"[Author] OR "Moeremans"[Author]) Filters: Publication date from 1990/01/01; English

72

Total with limits#7 "Animals"[Mesh] NOT "Humans"[Mesh] Filters: Publication date from

1990/01/01; English 2031836

#8 "Comment"[Publication Type] OR "Letter"[Publication Type] OR "Editorial"[Publication Type] Filters: Publication date from 1990/01/01; English

912003

#9 (#5 OR #6) NOT (#7 OR #8) Filters: Publication date from 1990/01/01; English

145

23

Table 7. Embase Search Strategy


Number of Articles

HIV/AIDS drug treatment#1 'human immunodeficiency virus infection'/exp/dm_dt OR 'anti human

immunodeficiency virus agent'/exp OR 'highly active antiretroviral therapy'/exp OR ('Human immunodeficiency virus infection'/exp AND ('drug therapy'/exp OR 'drug combination'/exp)) AND [english]/lim AND [embase]/lim AND [1990-2013]/py

90424

#2 ((('reverse transcriptase' NEXT/1 inhibitor*):ti OR NRTI*:ti OR NNRTI*:ti OR (protease NEXT/1 inhibitor*):ti OR PIs:ti OR (fusion NEXT/1 inhibitor*):ti OR FIs:ti OR (integrase NEXT/1 inhibitor*):ti OR (CCR5 NEXT/1 antagonist*):ti OR (anti NEXT/1 retroviral*):ti OR antiretroviral*:ti) AND (antiHIV:ti OR 'anti-HIV':ti OR HIV*:ti OR AIDS:ti) AND drug*:ti) OR ((antiHIV:ti OR 'anti-HIV':ti OR HIV*:ti) AND drug*:ti AND (treat*:ti OR therap*:ti)) AND [english]/lim AND [embase]/lim AND [1990-2013]/py

1828

#3 (#1 OR #2) NOT ('human immunodeficiency virus infection'/exp/mj/dm_pc OR prevent*:ti) AND [english]/lim AND [embase]/lim AND [1990-2013]/py

82748

Geographic area#4 #3 NOT ('Africa'/exp OR 'Asia'/exp OR 'South America'/exp OR 'Central

America'/exp) AND [english]/lim AND [embase]/lim AND [1990-2013]/py 75621

Economic/decision models#5 #4 AND ('pharmacoeconomics'/exp/mj OR 'drug cost'/exp/mj OR

'cost'/exp/mj OR 'economics'/exp/mj OR pharmacoeconomic*:ti OR cost*:ti OR economic*:ti) AND (evaluat*:ti OR (cost NEXT/1 effective*):ti OR utility:ti OR utilities:ti OR (cost NEXT/1 analy*):ti OR (cost NEXT/1 consequence*):ti OR 'decision tree'/exp/mj OR 'probability'/exp/mj OR (decision NEXT/1 analy*):ti OR 'decision support system'/exp/mj OR (decision NEXT/1 tree*):ti OR Markov:ti OR simulation*:ti OR discrete:ti OR 'computer simulation'/exp/mj OR decision*:ti) AND ('statistical model'/exp/mj OR model*:ti,ab) AND [english]/lim AND [embase]/lim AND [1990-2013]/py

141

Authors#6 #4 AND ('pharmacoeconomics'/exp/mj OR 'drug cost'/exp/mj OR

'cost'/exp/mj OR 'economics'/exp/mj OR pharmacoeconomic*:ti OR cost*:ti OR economic*:ti) AND ('statistical model'/exp/mj OR model*:ti,ab) AND (Mauskopf:au OR Freedberg:au OR Paltiel:au OR Braithwaite:au OR Justice:au OR Sanders:au OR Simpson:au OR Roberts:au OR Hornberger:au OR Schackman:au OR Sax:au OR Weinstein:au OR Yazdanpanah:au OR Moeremans:au) AND [english]/lim AND [embase]/lim AND [1990-2013]/py

59

Total with limits#7 'animal'/exp NOT 'human'/exp AND [english]/lim AND [embase]/lim AND

[1990-2013]/py 1828603

#8 Comment*:ti OR Letter:it OR Editorial:it AND [english]/lim AND [embase]/lim AND [1990-2013]/py

810714

#9 (#5 OR #6) NOT (#7 OR #8) AND [english]/lim AND [embase]/lim AND [1990-2013]/py

147

24

Table 8. Cochrane Library Search Strategy


Number of Articles

HIV/AIDS drug treatment#1 MeSH descriptor: [HIV Infections] explode all trees and with qualifiers: [Drug

therapy - DT]3432

#2 MeSH descriptor: [Anti-HIV Agents] explode all trees 2273#3 MeSH descriptor: [Antiretroviral Therapy, Highly Active] explode all trees 845#4 #1 or #2 or #3 3945#5 MeSH descriptor: [HIV Infections] explode all trees 6799#6 MeSH descriptor: [Drug Therapy] explode all trees 106866#7 MeSH descriptor: [Drug Combinations] this term only 8548#8 #5 and (#6 or #7) 2709#10 #4 or #8 4406#11 (("reverse transcriptase" next inhibitor* or NRTI* or NNRTI* or protease next

inhibitor* or PIs or fusion next inhibitor* or FIs or integrase next inhibitor* or CCR5 next antagonist* or anti next retroviral* or antiretroviral*) and (antiHIV or "anti HIV" or HIV* or AIDS) and drug*) or ((antiHIV or "anti HIV" or HIV*) and drug*) and (treat* or therap*):ti (Word variations have been searched)

152

#12 MeSH descriptor: [HIV Infections] explode all trees and with qualifiers: [Prevention & control - PC]

1580

#13 prevent*:ti (Word variations have been searched) 26170#14 (#10 or #11) not (#12 or #13) 3937Geographic area#15 MeSH descriptor: [Africa] explode all trees 3600#16 MeSH descriptor: [Asia] explode all trees 8536#17 MeSH descriptor: [South America] explode all trees 1185#18 MeSH descriptor: [Central America] explode all trees 173#19 #14 not (#15 or #16 or #17 or #18) 3592Economic/decision models#21 MeSH descriptor: [Economics] explode all trees 20000#22 MeSH descriptor: [Costs and Cost Analysis] explode all trees 18532#23 Any MeSH descriptor with qualifier(s): [Economics - EC] 17926#24 pharmacoeconomic* or cost* or economic*:ti (Word variations have been

searched)16979

#25 #21 or #23 or #24 25740#26 MeSH descriptor: [Decision Trees] explode all trees 752#27 MeSH descriptor: [Markov Chains] explode all trees 1501#28 MeSH descriptor: [Decision Support Techniques] explode all trees 2678

25


Number of Articles

#29 MeSH descriptor: [Computer Simulation] explode all trees 1181#30 evaluat* or cost next effective* or utility or utilities or cost next analy* or

cost next consequence* or decision next analy* or decision next tree* or Markov or simulation* or discrete or decision*:ti (Word variations have been searched)

41438

#31 #26 or #27 or #28 or #29 or #30 44158#32 MeSH descriptor: [Models, Economic] explode all trees 1458#33 MeSH descriptor: [Models, Statistical] explode all trees 11036#34 model*:ti (Word variations have been searched) 4749#35 #32 or #33 or #34 15165#37 #19 and #25 and #31 and #35 24Authors#38 Mauskopf or Freedberg or Paltiel or Braithwaite or Justice or Sanders or

Simpson or Roberts or Hornberger or Schackman or Sax or Weinstein or Yazdanpanah or Moeremans:au (Word variations have been searched)

5974

#39 #19 and #25 and #35 and #38 18Total#41 #37 or #39 28

26

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28

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29

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