title: Validation and calibration of a computer simulation model of pediatric HIV infection.
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.
authors.affiliation: Division of Infectious Diseases, Massachusetts General Hospital, Boston, Massachusetts, United States of America ; Medical Practice Evaluation Center, Massachusetts General Hospital, Boston, Massachusetts, United States of America ; Division of Infectious Diseases, Brigham and Women's Hospital, Boston, Massachusetts, United States of America.
authors.forename: Andrea L
authors.initials: AL
authors.lastname: Ciaranello
authors.affiliation: Division of General Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
authors.forename: Bethany L
authors.initials: BL
authors.lastname: Morris
authors.affiliation: Division of Infectious Diseases, Massachusetts General Hospital, Boston, Massachusetts, United States of America ; Division of General Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America ; Medical Practice Evaluation Center, Massachusetts General Hospital, Boston, Massachusetts, United States of America ; Division of Infectious Diseases, Brigham and Women's Hospital, Boston, Massachusetts, United States of America ; The Center for AIDS Research, Harvard University, Boston, Massachusetts, United States of America.
authors.forename: Rochelle P
authors.initials: RP
authors.lastname: Walensky
authors.affiliation: The Department of Health Policy and Management, Harvard School of Public Health, Boston, Massachusetts, United States of America.
authors.forename: Milton C
authors.initials: MC
authors.lastname: Weinstein
authors.affiliation: Department of Child Health and Pediatrics, Moi University, Eldoret, Kenya.
authors.forename: Samuel
authors.initials: S
authors.lastname: Ayaya
authors.affiliation: Division of General Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
authors.forename: Kathleen
authors.initials: K
authors.lastname: Doherty
authors.affiliation: Inserm, Unit 897, Institut de Santé Publique et de Développement, Université Bordeaux Segalen 2, Bordeaux, France.
authors.forename: Valeriane
authors.initials: V
authors.lastname: Leroy
authors.affiliation: Division of General Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
authors.forename: Taige
authors.initials: T
authors.lastname: Hou
authors.affiliation: Inserm, Unit 897, Institut de Santé Publique et de Développement, Université Bordeaux Segalen 2, Bordeaux, France.
authors.forename: Sophie
authors.initials: S
authors.lastname: Desmonde
authors.affiliation: Division of General Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
authors.forename: Zhigang
authors.initials: Z
authors.lastname: Lu
authors.affiliation: Division of General Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
authors.forename: Farzad
authors.initials: F
authors.lastname: Noubary
authors.affiliation: The Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America.
authors.forename: Kunjal
authors.initials: K
authors.lastname: Patel
authors.affiliation: Medical Practice Evaluation Center, Massachusetts General Hospital, Boston, Massachusetts, United States of America ; Children's Hospital Boston, Boston, Massachusetts, United States of America ; Department of Pediatrics, Division of Pediatric Infectious Diseases, University of California Los Angeles, Los Angeles, California, United States of America.
authors.forename: Lynn
authors.initials: L
authors.lastname: Ramirez-Avila
authors.affiliation: Division of General Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America ; Department of Medicine, and Department of Orthopedic Surgery, Brigham and Women's Hospital, Boston, Massachusetts, United States of America ; The Center for AIDS Research, Harvard University, Boston, Massachusetts, United States of America ; The Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America.
authors.forename: Elena
authors.initials: E
authors.lastname: Losina
authors.affiliation: The Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America.
authors.forename: George R
authors.initials: GR
authors.lastname: Seage
authors.affiliation: Division of Infectious Diseases, Massachusetts General Hospital, Boston, Massachusetts, United States of America ; Division of General Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America ; Medical Practice Evaluation Center, Massachusetts General Hospital, Boston, Massachusetts, United States of America ; The Center for AIDS Research, Harvard University, Boston, Massachusetts, United States of America ; The Department of Health Policy and Management, Harvard School of Public Health, Boston, Massachusetts, United States of America ; The Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts, United States of America.
authors.forename: Kenneth A
authors.initials: KA
authors.lastname: Freedberg
mesh_terms: D000293:Adolescent; D000349:Africa / Q000453:epidemiology; D002648:Child; D002675:Child, Preschool; D003198:Computer Simulation; D005260:Female; D015658:HIV Infections / Q000401:mortality* / Q000635:transmission*; D006801:Humans; D007223:Infant; D008297:Male; D008954:Models, Biological