Validation and calibration of a computer simulation model of pediatric HIV infection.

<h4>Background</h4>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 im...

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Autores principales:	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
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/575f44f4a66a4213b2b63291bd4836c7
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spelling	oai:doaj.org-article:575f44f4a66a4213b2b63291bd4836c72021-11-18T08:41:58ZValidation and calibration of a computer simulation model of pediatric HIV infection.1932-620310.1371/journal.pone.0083389https://doaj.org/article/575f44f4a66a4213b2b63291bd4836c72013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24349503/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Background</h4>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.<h4>Methods</h4>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.<h4>Results</h4>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.<h4>Conclusions</h4>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.Andrea L CiaranelloBethany L MorrisRochelle P WalenskyMilton C WeinsteinSamuel AyayaKathleen DohertyValeriane LeroyTaige HouSophie DesmondeZhigang LuFarzad NoubaryKunjal PatelLynn Ramirez-AvilaElena LosinaGeorge R SeageKenneth A FreedbergPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 12, p e83389 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q 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 Validation and calibration of a computer simulation model of pediatric HIV infection.
description	<h4>Background</h4>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.<h4>Methods</h4>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.<h4>Results</h4>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.<h4>Conclusions</h4>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.
format	article
author	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
author_facet	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
author_sort	Andrea L Ciaranello
title	Validation and calibration of a computer simulation model of pediatric HIV infection.
title_short	Validation and calibration of a computer simulation model of pediatric HIV infection.
title_full	Validation and calibration of a computer simulation model of pediatric HIV infection.
title_fullStr	Validation and calibration of a computer simulation model of pediatric HIV infection.
title_full_unstemmed	Validation and calibration of a computer simulation model of pediatric HIV infection.
title_sort	validation and calibration of a computer simulation model of pediatric hiv infection.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/575f44f4a66a4213b2b63291bd4836c7
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Validation and calibration of a computer simulation model of pediatric HIV infection.

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