Cost-effectiveness of Direct Antiviral Agents for Hepatitis C Virus Infection and a Combined Intervention of Syringe Access and Medication-assisted Therapy for Opioid Use Disorders in an Injection Drug Use Population.

BACKGROUND: There are too many plausible permutations and scale-up scenarios of combination hepatitis C virus (HCV) interventions for exhaustive testing in experimental trials. Therefore, we used a computer simulation to project the health and economic impacts of alternative combination intervention scenarios for people who inject drugs (PWID), focusing on direct antiviral agents (DAA) and medication-assisted treatment combined with syringe access programs (MAT+). METHODS: We performed an allocative efficiency study, using a mathematical model to simulate the progression of HCV in PWID and its related consequences. We combined 2 previously validated simulations to estimate the cost-effectiveness of intervention strategies that included a range of coverage levels. Analyses were performed from a health-sector and societal perspective, with a 15-year time horizon and a discount rate of 3%. RESULTS: From a health-sector perspective (excluding criminal justice system-related costs), 4 potential strategies fell on the cost-efficiency frontier. At 20% coverage, DAAs had an incremental cost-effectiveness ratio (ICER) of $27 251/quality-adjusted life-year (QALY). Combinations of DAA at 20% with MAT+ at 20%, 40%, and 80% coverage had ICERs of $165 985/QALY, $325 860/QALY, and $399 189/QALY, respectively. When analyzed from a societal perspective (including criminal justice system-related costs), DAA at 20% with MAT+ at 80% was the most effective intervention and was cost saving. While DAA at 20% with MAT+ at 80% was more expensive (eg, less cost saving) than MAT+ at 80% alone without DAA, it offered a favorable value compared to MAT+ at 80% alone ($23 932/QALY). CONCLUSIONS: When considering health-sector costs alone, DAA alone was the most cost-effective intervention. However, with criminal justice system-related costs, DAA and MAT+ implemented together became the most cost-effective intervention.

Cost-effectiveness of HIV care coordination scale-up among persons at high risk for sub-optimal HIV care outcomes.

BACKGROUND: A study of a comprehensive HIV Care Coordination Program (CCP) showed effectiveness in increasing viral load suppression (VLS) among PLWH in New York City (NYC). We evaluated the cost-effectiveness of a scale-up of the CCP in NYC. METHODS: We incorporated observed effects and costs of the CCP into a computer simulation of HIV in NYC, comparing strategy scale-up with no implementation. The simulation combined a deterministic compartmental model of HIV transmission with a stochastic microsimulation of HIV progression, and was calibrated to NYC HIV epidemiological data from 1997 to 2009. We assessed incremental cost-effectiveness from a health sector perspective using 2017 $US, a 20-year time horizon, and a 3% annual discount rate. We explored two scenarios: (1) two-year average enrollment and (2) continuous enrollment. RESULTS: In scenario 1, scale-up resulted in a cost-per-infection-averted of $898,104 and a cost-per-QALY-gained of $423,721. In sensitivity analyses, scale-up achieved cost-effectiveness if effectiveness increased from RR1.11 to RR1.37 or costs decreased by 41.7%. Limiting the intervention to persons with unsuppressed viral load prior to enrollment (RR1.32) attenuated the cost reduction necessary to 11.5%. In scenario 2, scale-up resulted in a cost-per-infection-averted of $705,171 and cost-per-QALY-gained of $720,970. In sensitivity analyses, scale-up achieved cost-effectiveness if effectiveness increased from RR1.11 to RR1.46 or program costs decreased by 71.3%. Limiting the intervention to persons with unsuppressed viral load attenuated the cost reduction necessary to 38.7%. CONCLUSION: Cost-effective CCP scale-up would require reduced costs and/or focused enrollment within NYC, but may be more readily achieved in cities with lower background VLS levels.

An Alternative Mathematical Modeling Approach to Estimating a Reference Life Expectancy.

Background. Reference life expectancies inform frequently used health metrics, which play an integral role in determining resource allocation and health policy decision making. Existing reference life expectancies are not able to account for variation in geographies, populations, and disease states. Using a computer simulation, we developed a reference life expectancy estimation that considers competing causes of mortality, and is tailored to population characteristics. Methods. We developed a Monte Carlo microsimulation model that explicitly represented the top causes of US mortality in 2014 and the risk factors associated with their onset. The microsimulation follows a birth cohort of hypothetical individuals resembling the population of the United States. To estimate a reference life expectancy, we compared current circumstances with an idealized scenario in which all modifiable risk factors were eliminated and adherence to evidence-based therapies was perfect. We compared estimations of years of potential years life lost with alternative approaches. Results. In the idealized scenario, we estimated that overall life expectancy in the United States would increase by 5.9 years to 84.7 years. Life expectancy for men would increase from 76.4 years to 82.5 years, and life expectancy for women would increase from 81.3 years to 86.8 years. Using age-75 truncation to estimate potential years life lost compared to using the idealized life expectancy underestimated potential health gains overall (38%), disproportionately underestimated potential health gains for women (by 70%) compared to men (by 40%), and disproportionately underestimated the importance of heart disease for white women and black men. Conclusion. Mathematical simulations can be used to estimate an idealized reference life expectancy among a population to better inform and assess progress toward targets to improve population health.

Measuring Population Health in a Large Integrated Health System to Guide Goal Setting and Resource Allocation: A Proof of Concept.

In integrated health care systems, techniques that identify successes and opportunities for targeted improvement are needed. The authors propose a new method for estimating population health that provides a more accurate and dynamic assessment of performance and priority setting. Member data from a large integrated health system (n = 96,246, 73.8% female, mean age = 44 ± 0.01 years) were used to develop a mechanistic mathematical simulation, representing the top causes of US mortality in 2014 and their associated risk factors. An age- and sex-matched US cohort served as comparator group. The simulation was recalibrated and retested for validity employing the outcome measure of 5-year mortality. The authors sought to estimate potential population health that could be gained by improving health risk factors in the study population. Potential gains were assessed using both average life years (LY) gained and average quality-adjusted life years (QALYs) gained. The simulation validated well compared to integrated health system data, producing an AUC (area under the curve) of 0.88 for 5-year mortality. Current population health was estimated as a life expectancy of 84.7 years or 69.2 QALYs. Comparing potential health gain in the US cohort to the Kaiser Permanente cohort, eliminating physical inactivity, unhealthy diet, smoking, and uncontrolled diabetes resulted in an increase of 1.5 vs. 1.3 LY, 1.1 vs. 0.8 LY, 0.5 vs. 0.2 LY, and 0.5 vs. 0.5 LY on average per person, respectively. Using mathematical simulations may inform efforts by integrated health systems to target resources most effectively, and may facilitate goal setting.

Cost-effectiveness of a combination strategy to enhance the HIV care continuum in Swaziland: Link4Health.

INTRODUCTION: Link4Health, a cluster-RCT, demonstrated the effectiveness of a combination strategy targeting barriers at various HIV continuum steps on linkage to and retention in care; showing effectiveness in achieving linkage to HIV care within 1 month plus retention in care at 12 months after HIV testing for people living with HIV (RR 1.48, 95% CI 1.19-1.96, p = 0.002). In addition to standard of care, Link4Health included: 1) Point-of-care CD4+ count testing; 2) Accelerated ART initiation; 3) Mobile phone appointment reminders; 4) Care and prevention package including commodities and informational materials; and 5) Non-cash financial incentive. Our objective was to evaluate the cost-effectiveness of a scale-up of the Link4Health strategy in Swaziland. METHODS AND FINDINGS: We incorporated the effects and costs of the Link4Health strategy into a computer simulation of the HIV epidemic in Swaziland, comparing a scenario where the strategy was scaled up to a scenario with no implementation. The simulation combined a deterministic compartmental model of HIV transmission with a stochastic microsimulation of HIV progression calibrated to Swaziland epidemiological data. It incorporated downstream health costs potentially saved and infections potentially prevented by improved linkage and treatment adherence. We assessed the incremental cost-effectiveness ratio of Link4Health compared to standard care from a health sector perspective reported in US$2015, a time horizon of 20 years, and a discount rate of 3% in accordance with WHO guidelines.[1] Our results suggest that scale-up of the Link4Health strategy would reduce new HIV infections over 20 years by 11,059 infections, a 7% reduction from the projected 169,019 cases and prevent 5,313 deaths, an 11% reduction from the projected 49,582 deaths. Link4Health resulted in an incremental cost per infection prevented of $13,310 and an incremental cost per QALY gained of $3,560/QALY from the health sector perspective. CONCLUSIONS: Using a threshold of <3 x per capita GDP, the Link4Health strategy is likely to be a cost-effective strategy for responding to the HIV epidemic in Swaziland.

Using value of information methods to determine the optimal sample size for effectiveness trials of alcohol interventions for HIV-infected patients in East Africa.

BACKGROUND: Unhealthy alcohol consumption exacerbates the HIV epidemic in East Africa. Potential benefits of new trials that test the effectiveness of alcohol interventions could not be evaluated by traditional sampling methods. Given the competition for health care resources in East Africa, this study aims to determine the optimal sample size given the opportunity cost of potentially re-allocating trial funds towards cost-effective alcohol treatments. METHODS: We used value of information methods to determine the optimal sample size by maximizing the expected net benefit of sampling for a hypothetical 2-arm intervention vs. control randomized trial, across ranges of policymaker's willingness-to-pay for the health benefit of an intervention. Probability distributions describing the relative likelihood of alternative trial results were imputed based on prior studies. In the base case, policymaker's willingness-to-pay was based on a simultaneously resource-constrained priority (routine HIV virological testing). Sensitivity analysis was performed for various willingness-to-pay thresholds and intervention durations. RESULTS: A new effectiveness trial accounting for the benefit of more precise decision-making on alcohol intervention implementation would benefit East Africa $67,000 with the optimal sample size of 100 persons per arm under the base case willingness-to-pay threshold and intervention duration of 20 years. At both a conservative willingness-to-pay of 1 x GDP/capita and a high willingness-to-pay of 3 x GDP/capita for an additional health gain added by an alcohol intervention, a new trial was not recommended due to limited decision uncertainty. When intervention duration was 10 or 5 years, there was no return on investment across suggested willingness-to-pay thresholds. CONCLUSIONS: Value of information methods could be used as an alternative approach to assist the efficient design of alcohol trials. If reducing unhealthy alcohol use is a long-term goal for HIV programs in East Africa, additional new trials with optimal sample sizes ranging from 100 to 250 persons per arm could save the opportunity cost of implementing less cost-effective alcohol strategies in HIV prevention. Otherwise, conducting a new trial is not recommended.

Cost-Effectiveness of Peer- Versus Venue-Based Approaches for Detecting Undiagnosed HIV Among Heterosexuals in High-Risk New York City Neighborhoods.

INTRODUCTION: We used a computer simulation of HIV progression and transmission to evaluate the cost-effectiveness of a scale-up of 3 strategies to seek out and test individuals with undiagnosed HIV in New York City (NYC). SETTING: Hypothetical NYC population. METHODS: We incorporated the observed effects and costs of the 3 "seek and test" strategies in a computer simulation of HIV in NYC, comparing a scenario in which the strategies were scaled up with a 1-year implementation or a long-term implementation with a counterfactual scenario with no scale-up. The simulation combined a deterministic compartmental model of HIV transmission with a stochastic microsimulation of HIV progression, calibrated to NYC epidemiological data from 2003 to 2015. The 3 approaches were respondent-driven sampling (RDS) with anonymous HIV testing ("RDS-A"), RDS with a 2-session confidential HIV testing approach ("RDS-C"), and venue-based sampling ("VBS"). RESULTS: RDS-A was the most cost-effective strategy tested. When implemented for only 1 year and then stopped thereafter, using a societal perspective, the cost per quality-adjusted life-year (QALY) gained versus no intervention was $812/QALY, $18,110/QALY, and $20,362/QALY for RDS-A, RDS-C, and VBS, respectively. When interventions were implemented long term, the cost per QALY gained versus no intervention was cost-saving, $31,773/QALY, and $35,148/QALY for RDS-A, RDS-C, and VBS, respectively. When compared with RDS-A, the incremental cost-effectiveness ratios for both VBS and RDS-C were dominated. CONCLUSIONS: The expansion of the RDS-A strategy would substantially reduce HIV-related deaths and new HIV infections in NYC, and would be either cost-saving or have favorable cost-effectiveness.

Economic evaluation of mobile phone text message interventions to improve adherence to HIV therapy in Kenya.

BACKGROUND: A surge in mobile phone availability has fueled low cost short messaging service (SMS) adherence interventions. Multiple systematic reviews have concluded that some SMS-based interventions are effective at improving antiretroviral therapy (ART) adherence, and they are hypothesized to improve retention in care. The objective of this study was to evaluate the cost-effectiveness of SMS-based adherence interventions and explore the added value of retention benefits. METHODS: We evaluated the cost-effectiveness of weekly SMS interventions compared to standard care among HIV+ individuals initiating ART for the first time in Kenya. We used an individual level micro-simulation model populated with data from two SMS-intervention trials, an East-African HIV+ cohort and published literature. We estimated average quality adjusted life years (QALY) and lifetime HIV-related costs from a healthcare perspective. We explored a wide range of scenarios and assumptions in one-way and multivariate sensitivity analyses. RESULTS: We found that SMS-based adherence interventions were cost-effective by WHO standards, with an incremental cost-effectiveness ratio (ICER) of $1,037/QALY. In the secondary analysis, potential retention benefits improved the cost-effectiveness of SMS intervention (ICER = $864/QALY). In multivariate sensitivity analyses, the interventions remained cost-effective in most analyses, but the ICER was highly sensitive to intervention costs, effectiveness and average cohort CD4 count at ART initiation. SMS interventions remained cost-effective in a test and treat scenario where individuals were assumed to initiate ART upon HIV detection. CONCLUSIONS: Effective SMS interventions would likely increase the efficiency of ART programs by improving HIV treatment outcomes at relatively low costs, and they could facilitate achievement of the UNAIDS goal of 90% viral suppression among those on ART by 2020.

Evaluating the impact of prioritization of antiretroviral pre-exposure prophylaxis in New York.

OBJECTIVE: To compare the value and effectiveness of different prioritization strategies of pre-exposure prophylaxis (PrEP) in New York City (NYC). DESIGN: Mathematical modelling utilized as clinical trial is not feasible. METHODS: Using a model accounting for both sexual and parenteral transmission of HIV, we compare different PrEP prioritization strategies (PPS) with two scenarios ­ no PrEP and PrEP for all susceptible at-risk individuals. The PPS included PrEP for all MSM,only high-risk MSM, high-risk heterosexuals, and IDUs, and all combinations of these four strategies. Outcomes included HIV infections averted, and incremental cost effectiveness(per-infection averted) ratios. Initial assumptions regarding PrEP included a 44% reduction in HIV transmission, 50% uptake in the prioritized population and an annual cost per person of $9762. Sensitivity analyses on key parameters were conducted. RESULTS: Prioritization to all MSM results in a 19% reduction in new HIV infections. Compared with PrEP for all persons at-risk, this PPS retains 79% of the preventive effect at 15% of the total cost. PrEP prioritized to only high-risk MSM results in a reduction in new HIV infections of 15%. This PPS retains 60% of the preventive effect at 6% of the total cost. There are diminishing returns when PrEP utilization is expanded beyond this group. CONCLUSION: PrEP implementation is relatively cost-inefficient under our initial assumptions. Our results suggest that PrEP should first be promoted among MSM who are at particularly high risk of HIV acquisition. Further expansion beyond this group may be cost-effective, but is unlikely to be cost-saving.

Cost-effectiveness of different strategies to monitor adults on antiretroviral treatment: a combined analysis of three mathematical models.

BACKGROUND: WHO's 2013 revisions to its Consolidated Guidelines on antiretroviral drugs recommend routine viral load monitoring, rather than clinical or immunological monitoring, as the preferred monitoring approach on the basis of clinical evidence. However, HIV programmes in resource-limited settings require guidance on the most cost-effective use of resources in view of other competing priorities such as expansion of antiretroviral therapy coverage. We assessed the cost-effectiveness of alternative patient monitoring strategies. METHODS: We evaluated a range of monitoring strategies, including clinical, CD4 cell count, and viral load monitoring, alone and together, at different frequencies and with different criteria for switching to second-line therapies. We used three independently constructed and validated models simultaneously. We estimated costs on the basis of resource use projected in the models and associated unit costs; we quantified impact as disability-adjusted life years (DALYs) averted. We compared alternatives using incremental cost-effectiveness analysis. FINDINGS: All models show that clinical monitoring delivers significant benefit compared with a hypothetical baseline scenario with no monitoring or switching. Regular CD4 cell count monitoring confers a benefit over clinical monitoring alone, at an incremental cost that makes it affordable in more settings than viral load monitoring, which is currently more expensive. Viral load monitoring without CD4 cell count every 6-12 months provides the greatest reductions in morbidity and mortality, but incurs a high cost per DALY averted, resulting in lost opportunities to generate health gains if implemented instead of increasing antiretroviral therapy coverage or expanding antiretroviral therapy eligibility. INTERPRETATION: The priority for HIV programmes should be to expand antiretroviral therapy coverage, firstly at CD4 cell count lower than 350 cells per µL, and then at a CD4 cell count lower than 500 cells per µL, using lower-cost clinical or CD4 monitoring. At current costs, viral load monitoring should be considered only after high antiretroviral therapy coverage has been achieved. Point-of-care technologies and other factors reducing costs might make viral load monitoring more affordable in future. FUNDING: Bill & Melinda Gates Foundation, WHO.

Impact of interventions targeting unhealthy alcohol use in Kenya on HIV transmission and AIDS-related deaths.

BACKGROUND: HIV remains a major cause of preventable morbidity and mortality in Kenya. The effects of behaviors that accompany unhealthy alcohol consumption are a pervasive risk factor for HIV transmission and progression. Our objective was to estimate the portion of HIV infections attributable to unhealthy alcohol use and to evaluate the impact of hypothetical interventions directed at unhealthy alcohol use on HIV infections and deaths. METHODS: We estimated outcomes over a time horizon of 20 years using a computer simulation of the Kenyan population. This computer simulation integrates a compartmental model of HIV transmission with a mechanistic model of HIV progression that was previously validated in sub-Saharan Africa. Integration of the transmission and progression models allows simultaneous consideration of alcohol's effects on HIV transmission and progression (e.g., lowering antiretroviral adherence may increase transmission risk by elevating viral load, and may simultaneously increase progression by increasing the likelihood of AIDS). The simulation considers important aspects of heterogeneous sexual mixing patterns, including assortativeness of partners by age and activity level, age-discordant relationships, and high activity subgroups. Outcomes included number of new HIV infections, number of AIDS deaths, and infectivity (number of new infections per infected person per year). RESULTS: Our model estimated that the effects of behaviors accompanying unhealthy alcohol consumption are responsible for 13.0% of new HIV infections in Kenya. An alcohol intervention with effectiveness similar to that observed in a published randomized controlled trial of a cognitive-behavioral therapy-based intervention in Kenya (45% reduction in unhealthy alcohol consumption) could prevent nearly half of these infections, reducing their number by 69,858 and reducing AIDS deaths by 17,824 over 20 years. Estimates were sensitive to assumptions with respect to the magnitude of alcohol's underlying effects on condom use, antiretroviral therapy adherence, and sexually transmitted infection prevalence. CONCLUSIONS: A substantial number of new HIV infections in Kenya are attributable to unhealthy alcohol use. An alcohol intervention with the effectiveness observed in a published randomized controlled trial has the potential to reduce infections over 20 years by nearly 5% and avert nearly 18,000 deaths related to HIV.

How do different eligibility guidelines for antiretroviral therapy affect the cost-effectiveness of routine viral load testing in sub-Saharan Africa?

BACKGROUND: Increased eligibility guidelines of antiretroviral therapy (ART) may lead to greater routine viral load monitoring. However, in resource-constrained settings, the additional resources required by greater routine viral load monitoring may impair ability to comply with expanded eligibility guidelines for ART. OBJECTIVE: We use a published validated computer simulation of the HIV epidemic in East African countries (expanded to include transmission as well as disease progression) to evaluate the cost-effectiveness of routine viral load monitoring. METHODS: We explored alternative scenarios regarding cost, frequency, and switching threshold of routine viral load monitoring (including every 6 or every 12 months; and switching thresholds of 1000, or 10 000 copies/ml), as well as alternative scenarios regarding ART initiation (200, 350, 500  cells/µl, and no CD4 cell threshold). For each ART initiation strategy, we sought to identify the viral load monitoring strategy at which the incremental cost-effectiveness ratio (ICER) of more frequent routine viral load testing became more favorable than the ICER of more expansive ART eligibility. Cost inputs were based on data provided by the Academic Model Providing Access to Healthcare (AMPATH), and disease progression inputs were based on prior published work. We used a discount rate of 3%, a time horizon of 20 years, and a payer perspective. RESULTS: Across a wide range of scenarios, and even when considering the beneficial effect of virological monitoring at reducing HIV transmission, earlier ART initiation conferred far greater health benefits for resources spent than routine virological testing, with ICERs of approximately $1000 to $2000 for earlier ART initiation, versus ICERs of approximately $5000 to $25 000 for routine virological monitoring. ICERs of viral load testing were insensitive to the cost of the viral load test, because most of the costs originated from the downstream higher costs of later regimens. ICERs of viral load testing were very sensitive to the relative cost of second-line compared with first-line regimens, assuming favorable value when the costs of these regimens were equal. CONCLUSION: If all HIV patients are not yet treated with ART starting at 500  cells/µl and costs of second regimens remain substantially more expensive than first-line regimens, resources would buy more population health if they are spent on earlier ART rather than being spent on routine virological testing.

Averting HIV infections in New York City: a modeling approach estimating the future impact of additional behavioral and biomedical HIV prevention strategies.

BACKGROUND: New York City (NYC) remains an epicenter of the HIV epidemic in the United States. Given the variety of evidence-based HIV prevention strategies available and the significant resources required to implement each of them, comparative studies are needed to identify how to maximize the number of HIV cases prevented most economically. METHODS: A new model of HIV disease transmission was developed integrating information from a previously validated micro-simulation HIV disease progression model. Specification and parameterization of the model and its inputs, including the intervention portfolio, intervention effects and costs were conducted through a collaborative process between the academic modeling team and the NYC Department of Health and Mental Hygiene. The model projects the impact of different prevention strategies, or portfolios of prevention strategies, on the HIV epidemic in NYC. RESULTS: Ten unique interventions were able to provide a prevention benefit at an annual program cost of less than $360,000, the threshold for consideration as a cost-saving intervention (because of offsets by future HIV treatment costs averted). An optimized portfolio of these specific interventions could result in up to a 34% reduction in new HIV infections over the next 20 years. The cost-per-infection averted of the portfolio was estimated to be $106,378; the total cost was in excess of $2 billion (over the 20 year period, or approximately $100 million per year, on average). The cost-savings of prevented infections was estimated at more than $5 billion (or approximately $250 million per year, on average). CONCLUSIONS: Optimal implementation of a portfolio of evidence-based interventions can have a substantial, favorable impact on the ongoing HIV epidemic in NYC and provide future cost-saving despite significant initial costs.

Alternative antiretroviral monitoring strategies for HIV-infected patients in east Africa: opportunities to save more lives?

BACKGROUND: Updated World Health Organization guidelines have amplified debate about how resource constraints should impact monitoring strategies for HIV-infected persons on combination antiretroviral therapy (cART). We estimated the incremental benefit and cost effectiveness of alternative monitoring strategies for east Africans with known HIV infection. METHODS: Using a validated HIV computer simulation based on resource-limited data (USAID and AMPATH) and circumstances (east Africa), we compared alternative monitoring strategies for HIV-infected persons newly started on cART. We evaluated clinical, immunologic and virologic monitoring strategies, including combinations and conditional logic (e.g., only perform virologic testing if immunologic testing is positive). We calculated incremental cost-effectiveness ratios (ICER) in units of cost per quality-adjusted life year (QALY), using a societal perspective and a lifetime horizon. Costs were measured in 2008 US dollars, and costs and benefits were discounted at 3%. We compared the ICER of monitoring strategies with those of other resource-constrained decisions, in particular earlier cART initiation (at CD4 counts of 350 cells/mm3 rather than 200 cells/mm3). RESULTS: Monitoring strategies employing routine CD4 testing without virologic testing never maximized health benefits, regardless of budget or societal willingness to pay for additional health benefits. Monitoring strategies employing virologic testing conditional upon particular CD4 results delivered the most benefit at willingness-to-pay levels similar to the cost of earlier cART initiation (approximately $2600/QALY). Monitoring strategies employing routine virologic testing alone only maximized health benefits at willingness-to-pay levels (> $4400/QALY) that greatly exceeded the ICER of earlier cART initiation. CONCLUSIONS: CD4 testing alone never maximized health benefits regardless of resource limitations. Programmes routinely performing virologic testing but deferring cART initiation may increase health benefits by reallocating monitoring resources towards earlier cART initiation.

Using mechanistic models to simulate comparative effectiveness trials of therapy and to estimate long-term outcomes in HIV care.

BACKGROUND: In HIV care, it is difficult to decide when to initiate therapy, which drugs to use for initial treatment, and which drugs to use if drug resistance develops. With hundreds of possible drug regimens available and variable patterns of drug resistance, randomized controlled trials cannot answer all HIV treatment decisions. Mechanistic models of HIV infection can be used to conduct virtual therapeutic trials with the goal of predicting outcomes, some of which are long-term and may not fall within the time frame of a typical therapeutic trial. METHODS: We used a previously developed and validated model of HIV infection to replicate 2 arms of an HIV initial treatment trial (ACTG A5142) and predict long-term outcomes. The model incorporated data about biologic processes involved in the development of drug resistance. RESULTS: The model reproduced the proportion that developed AIDS (0.04 and 0.05 for the efavirenz arm and lopinavir arms, respectively, vs. 0.04 and 0.06 for the trial), the development of virologic failure (0.27 and 0.33 for the Efavirenz arm and lopinavir arms, respectively, vs. 0.24 and 0.37 for the trial), and drug resistance. The hazard ratio for the time to treatment failure, a combination of resistance and other causes (0.96 for the model vs. 0.75 for the trial; 95% confidence interval, 0.57-0.98), and changes in CD4 cell count, were less accurate. The model estimated longer-term life expectancy, quality-adjusted life expectancy, and HIV-related deaths. CONCLUSIONS: Mechanistic models of HIV infections have the potential to be useful in comparative effectiveness research.