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Home >> Publications >> Validation and Calibration of a Computer Simulation Model of Pediatric HIV Infection.

Publication

Author(s):

Ciaranello AL, Morris BL, Walensky RP, Weinstein MC, Ayaya S, Doherty K, Leroy V, Hou T, Desmonde S, Lu Z, Noubary F, Patel K, Ramirez-Avila L, Losina E, Seage Iii GR, Freedberg KA.

Pub Title:

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

Pub Date:

Dec 13 2013

Pub Region(s):

East Africa

Journal:

Title: 
PLoS One
Link: 
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3862684/

PubMed: 24349503
Pub PDF: PDF icon 24349503.pdf

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.

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Citation:

Ciaranello AL, Morris BL, Walensky RP, Weinstein MC, Ayaya S, Doherty K, Leroy V, Hou T, Desmonde S, Lu Z, Noubary F, Patel K, Ramirez-Avila L, Losina E, Seage Iii GR, Freedberg KA. Validation and Calibration of a Computer Simulation Model of Pediatric HIV Infection. PLoS One. 2013;8(12):e83389. doi: 10.1371/journal.pone.0083389. PubMed PMID: 24349503; PubMed Central PMCID: PMC3862684.