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An In Vitro Model for Measuring Immune Responses to Malaria in the Context of HIV Co-infection
Published on: October 6, 2015
Validation and calibration of a computer simulation model of pediatric HIV infection
Andrea L Ciaranello1, Bethany L Morris2, Rochelle P Walensky3
1Division 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.
Insights
This study developed and validated the CEPAC-Pediatric model for projecting HIV progression in children. The model accurately predicts survival outcomes, crucial for informing pediatric HIV treatment strategies.
Area of Science:
- Pediatric infectious diseases
- Computational epidemiology
- Public health modeling
Background:
- Computer simulation models are vital for projecting long-term patient outcomes and informing health policy.
- Accurate models are needed to evaluate pediatric HIV treatment strategies.
Purpose of the Study:
- To internally validate and calibrate a patient-level model (CEPAC-Pediatric) for HIV progression in untreated children.
- To provide a framework for comparing pediatric HIV treatment strategies.
Main Methods:
- Developed a Monte Carlo patient-level model (CEPAC-Pediatric) using data from IeDEA and WITS.
- Internally validated the model using root-mean square error (RMSE) <0.01 against empirical survival data.
- Calibrated the model to African settings using UNAIDS data.
Main Results:
- The CEPAC-Pediatric model demonstrated good internal validation, with modeled survival at 16 months (91.2%) closely matching observed survival (91.1%).
- The best-fit parameter set involved a 45% CD4% at birth and specific monthly decline rates.
- Calibration required increased modeled mortality risks to align with UNAIDS survival data.
Conclusions:
- The CEPAC-Pediatric model performed well in internal validation.
- Adjustments in modeled mortality risks underscore the significance of pre-enrollment mortality in pediatric cohort studies.
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.
