Background US HIV treatment guidelines recommend branded once-daily, one-pill efavirenz/emtricitabine/tenofovir as preferred first-line antiretroviral treatment (ART). With the anticipated approval of generic efavirenz in 2012 in the US, the cost of a once-daily, three-pill alternative (generic efavirenz, generic lamivudine, tenofovir) will decrease, but adherence and virologic suppression may be reduced. Objectives To assess the clinical impact, costs, and cost-effectiveness of the generic-based three-pill regimen compared to the branded, co-formulated regimen. To project the potential national savings in the first year of a switch to generic-based ART. Design Mathematical simulation of HIV disease. Data Sources Published data from US clinical trials and observational cohorts. Target Population HIV-infected patients eligible to start on or switch to an efavirenz-based generic ART regimen. Time Horizon Lifetime, One-year Perspective US health system Interventions No ART (for comparison), Three-pill Generic ART, and Branded ART Outcome Measures Quality-adjusted life expectancy, costs, and incremental cost-effectiveness ratios (ICER, $/quality-adjusted life expectancy [QALY]). Results of Base-Case Analysis Compared to No ART, Generic ART has an ICER of $21,100/QALY. Compared to Generic ART, Branded ART increases lifetime costs by $42,500, and per-person survival gains by 0.37 QALYs, for an ICER of $114,800/QALY. Estimated first-year savings, if all eligible US patients start on or switch to Generic ART, are $920 million. Results of Sensitivity Analysis Most plausible assumptions about Generic ART efficacy and costs lead to Branded ART ICERs >$100,000/QALY. Limitations The efficacy and price reduction associated with generics are unknown; estimates are intended to be conservative. Conclusions Compared to a slightly less effective generic-based regimen, the cost-effectiveness of first-line Branded ART exceeds $100,000/QALY. Generic-based ART in the US could yield substantial budgetary savings to HIV programs.

Emily Hyle and colleagues conduct a cost-effectiveness analysis to estimate the clinical and economic impact of point-of-care CD4 testing compared to laboratory-based tests in Mozambique. Please see later in the article for the Editors' Summary

Understanding HIV transmission dynamics is critical to estimating the potential population-wide impact of HIV prevention and treatment interventions. We developed an individual-based simulation model of the heterosexual HIV epidemic in South Africa and linked it to the previously published Cost-Effectiveness of Preventing AIDS Complications (CEPAC) International Model, which simulates the natural history and treatment of HIV. In this new model, the CEPAC Dynamic Model (CDM), the probability of HIV transmission per sexual encounter between short-term, long-term and commercial sex worker partners depends upon the HIV RNA and disease stage of the infected partner, condom use, and the circumcision status of the uninfected male partner. We included behavioral, demographic and biological values in the CDM and calibrated to HIV prevalence in South Africa pre-antiretroviral therapy. Using a multi-step fitting procedure based on Bayesian melding methodology, we performed 264,225 simulations of the HIV epidemic in South Africa and identified 3,750 parameter sets that created an epidemic and had behavioral characteristics representative of a South African population pre-ART. Of these parameter sets, 564 contributed 90% of the likelihood weight to the fit, and closely reproduced the UNAIDS HIV prevalence curve in South Africa from 1990–2002. The calibration was sensitive to changes in the rate of formation of short-duration partnerships and to the partnership acquisition rate among high-risk individuals, both of which impacted concurrency. Runs that closely fit to historical HIV prevalence reflect diverse ranges for individual parameter values and predict a wide range of possible steady-state prevalence in the absence of interventions, illustrating the value of the calibration procedure and utility of the model for evaluating interventions. This model, which includes detailed behavioral patterns and HIV natural history, closely fits HIV prevalence estimates.

Background. Metamodels can simplify complex health policy models and yield instantaneous results to inform policy decisions. We investigated the predictive validity of linear regression metamodels used to support a real-time decision-making tool that compares infant HIV testing/screening strategies. Methods. We developed linear regression metamodels of the Cost-Effectiveness of Preventing AIDS Complications Pediatric (CEPAC-P) microsimulation model used to predict life expectancy and lifetime HIV-related costs/person of two infant HIV testing/screening programs in South Africa. Metamodel performance was assessed with cross-validation and Bland-Altman plots, showing between-method differences in predicted outcomes against their means. Predictive validity was determined by the percentage of simulations in which the metamodels accurately predicted the strategy with the greatest net health benefit (NHB) as projected by the CEPAC-P model. We introduced a zone of indifference and investigated the width needed to produce between-method agreement in 95% of the simulations. We also calculated NHB losses from “wrong” decisions by the metamodel. Results. In cross-validation, linear regression metamodels accurately approximated CEPAC-P-projected outcomes. For life expectancy, Bland-Altman plots showed good agreement between CEPAC-P and the metamodel (within 1.1 life-months difference). For costs, 95% of between-method differences were within $65/person. The metamodels predicted the same optimal strategy as the CEPAC-P model in 87.7% of simulations, increasing to 95% with a zone of indifference of 0.24 life-months ( ∼ 7 days). The losses in health benefits due to “wrong” choices by the metamodel were modest (range: 0.0002–1.1 life-months). Conclusions. For this policy question, linear regression metamodels offered sufficient predictive validity for the optimal testing strategy as compared with the CEPAC-P model. Metamodels can simulate different scenarios in real time, based on sets of input parameters that can be depicted in a widely accessible decision-support tool.

A comprehensive simulation of lifetime course of HIV in the USA indicated that using LPV/r as first-line therapy compared with DRV + RTV may result in cost savings, with similar clinical outcomes.