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http://ir.mu.ac.ke:8080/jspui/handle/123456789/6955
Title: | Validation and calibration of a computer simulation model of pediatric HIV infection |
Authors: | Ciaranello, Andrea L. Morris, Bethany L. Walensky, Rochelle P. Weinstein, Milton C. Ayaya, Samuel Doherty, Kathleen Leroy, Valeriane Hou, Taige Desmonde, Sophie Lu, Zhigang Noubary, Farzad Patel, Kunjal Ramirez-Avila, Lynn Losina, Elena Seage, George R. Freedberg, Kenneth A |
Keywords: | Computer simulation Health policy HIV disease Pediatric Antiretroviral therapy |
Issue Date: | 13-Dec-2013 |
Publisher: | PLOS ONE |
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 <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. |
URI: | http://ir.mu.ac.ke:8080/jspui/handle/123456789/6955 |
Appears in Collections: | School of Medicine |
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