PLoS ONE (Jan 2013)

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,
  • Kenneth A Freedberg

DOI
https://doi.org/10.1371/journal.pone.0083389
Journal volume & issue
Vol. 8, no. 12
p. e83389

Abstract

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BackgroundComputer 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.MethodsWe developed a patient-level (Monte Carlo) model of HIV progression among untreated children 1,300 untreated, HIV-infected African children.ResultsIn 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.ConclusionsThe 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.