Validation and Calibration of a Computer Simulation Model of Pediatric HIV Infection

Andrea L Ciaranello, Bethany L Morris, Rochelle P Walensky, Milton C Weinstein, Samuel Ayaya, Kathleen Doherty, Valeriane Leroy, Taige Hou, Sophie Desmonde, Zhigang Lu, Farzad Noubary, Kunjal Patel, Lynn Ramirez-Avila, Elena Losina, George R Seage and Kenneth A Freedberg

PLOS ONE, 2013, vol. 8, issue 12, 1-

Abstract: 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 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.

Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0083389

DOI: 10.1371/journal.pone.0083389

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