Person:

Doherty, Kathleen

Background: Computer simulation models can project long-term patient outcomes and inform health policy. We internally validated and then calibrated a model of HIV disease in children before initiation of antiretroviral therapy to provide a framework against which to compare the impact of pediatric HIV treatment strategies. Methods: We developed a patient-level (Monte Carlo) model of HIV progression among untreated children <5 years of age, using the Cost-Effectiveness of Preventing AIDS Complications model framework: the CEPAC-Pediatric model. We populated the model with data on opportunistic infection and mortality risks from the International Epidemiologic Database to Evaluate AIDS (IeDEA), with mean CD4% at birth (42%) and mean CD4% decline (1.4%/month) from the Women and Infants’ Transmission Study (WITS). We internally validated the model by varying WITS-derived CD4% data, comparing the corresponding model-generated survival curves to empirical survival curves from IeDEA, and identifying best-fitting parameter sets as those with a root-mean square error (RMSE) <0.01. We then calibrated the model to other African settings by systematically varying immunologic and HIV mortality-related input parameters. Model-generated survival curves for children aged 0-60 months were compared, again using RMSE, to UNAIDS data from >1,300 untreated, HIV-infected African children. Results: In internal validation analyses, model-generated survival curves fit IeDEA data well; modeled and observed survival at 16 months of age were 91.2% and 91.1%, respectively. RMSE varied widely with variations in CD4% parameters; the best fitting parameter set (RMSE = 0.00423) resulted when CD4% was 45% at birth and declined by 6%/month (ages 0-3 months) and 0.3%/month (ages >3 months). In calibration analyses, increases in IeDEA-derived mortality risks were necessary to fit UNAIDS survival data. Conclusions: The CEPAC-Pediatric model performed well in internal validation analyses. Increases in modeled mortality risks required to match UNAIDS data highlight the importance of pre-enrollment mortality in many pediatric cohort studies.

Background: Pediatric antiretroviral therapy (ART) has been shown to substantially reduce morbidity and mortality in HIV-infected infants and children. To accurately project program costs, analysts need accurate estimations of antiretroviral drug (ARV) costs for children. However, the costing of pediatric antiretroviral therapy is complicated by weight-based dosing recommendations which change as children grow. Methods: We developed a step-by-step methodology for estimating the cost of pediatric ARV regimens for children ages 0–13 years old. The costing approach incorporates weight-based dosing recommendations to provide estimated ARV doses throughout childhood development. Published unit drug costs are then used to calculate average monthly drug costs. We compared our derived monthly ARV costs to published estimates to assess the accuracy of our methodology. Results: The estimates of monthly ARV costs are provided for six commonly used first-line pediatric ARV regimens, considering three possible care scenarios. The costs derived in our analysis for children were fairly comparable to or slightly higher than available published ARV drug or regimen estimates. Conclusions: The methodology described here can be used to provide an accurate estimation of pediatric ARV regimen costs for cost-effectiveness analysts to project the optimum packages of care for HIV-infected children, as well as for program administrators and budget analysts who wish to assess the feasibility of increasing pediatric ART availability in constrained budget environments.