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EPICE-HIV: An Epidemiologic Cost-Effectiveness Model for HIV Treatment

The goal of this research was to establish a new and innovative framework for cost-effectiveness modeling of HIV-1 treatment, simultaneously considering both clinical and epidemiological outcomes. EPICE-HIV is a multi-paradigm model based on a within-host micro-simulation model for the disease progr...

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Autores principales: Vandewalle, Björn, Llibre, Josep M., Parienti, Jean-Jacques, Ustianowski, Andrew, Camacho, Ricardo, Smith, Colette, Miners, Alec, Ferreira, Diana, Félix, Jorge
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4752501/
https://www.ncbi.nlm.nih.gov/pubmed/26870960
http://dx.doi.org/10.1371/journal.pone.0149007
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author Vandewalle, Björn
Llibre, Josep M.
Parienti, Jean-Jacques
Ustianowski, Andrew
Camacho, Ricardo
Smith, Colette
Miners, Alec
Ferreira, Diana
Félix, Jorge
author_facet Vandewalle, Björn
Llibre, Josep M.
Parienti, Jean-Jacques
Ustianowski, Andrew
Camacho, Ricardo
Smith, Colette
Miners, Alec
Ferreira, Diana
Félix, Jorge
author_sort Vandewalle, Björn
collection PubMed
description The goal of this research was to establish a new and innovative framework for cost-effectiveness modeling of HIV-1 treatment, simultaneously considering both clinical and epidemiological outcomes. EPICE-HIV is a multi-paradigm model based on a within-host micro-simulation model for the disease progression of HIV-1 infected individuals and an agent-based sexual contact network (SCN) model for the transmission of HIV-1 infection. It includes HIV-1 viral dynamics, CD4(+) T cell infection rates, and pharmacokinetics/pharmacodynamics modeling. Disease progression of HIV-1 infected individuals is driven by the interdependent changes in CD4(+) T cell count, changes in plasma HIV-1 RNA, accumulation of resistance mutations and adherence to treatment. The two parts of the model are joined through a per-sexual-act and viral load dependent probability of disease transmission in HIV-discordant couples. Internal validity of the disease progression part of the model is assessed and external validity is demonstrated in comparison to the outcomes observed in the STaR randomized controlled clinical trial. We found that overall adherence to treatment and the resulting pattern of treatment interruptions are key drivers of HIV-1 treatment outcomes. Our model, though largely independent of efficacy data from RCT, was accurate in producing 96-week outcomes, qualitatively and quantitatively comparable to the ones observed in the STaR trial. We demonstrate that multi-paradigm micro-simulation modeling is a promising tool to generate evidence about optimal policy strategies in HIV-1 treatment, including treatment efficacy, HIV-1 transmission, and cost-effectiveness analysis.
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spelling pubmed-47525012016-02-26 EPICE-HIV: An Epidemiologic Cost-Effectiveness Model for HIV Treatment Vandewalle, Björn Llibre, Josep M. Parienti, Jean-Jacques Ustianowski, Andrew Camacho, Ricardo Smith, Colette Miners, Alec Ferreira, Diana Félix, Jorge PLoS One Research Article The goal of this research was to establish a new and innovative framework for cost-effectiveness modeling of HIV-1 treatment, simultaneously considering both clinical and epidemiological outcomes. EPICE-HIV is a multi-paradigm model based on a within-host micro-simulation model for the disease progression of HIV-1 infected individuals and an agent-based sexual contact network (SCN) model for the transmission of HIV-1 infection. It includes HIV-1 viral dynamics, CD4(+) T cell infection rates, and pharmacokinetics/pharmacodynamics modeling. Disease progression of HIV-1 infected individuals is driven by the interdependent changes in CD4(+) T cell count, changes in plasma HIV-1 RNA, accumulation of resistance mutations and adherence to treatment. The two parts of the model are joined through a per-sexual-act and viral load dependent probability of disease transmission in HIV-discordant couples. Internal validity of the disease progression part of the model is assessed and external validity is demonstrated in comparison to the outcomes observed in the STaR randomized controlled clinical trial. We found that overall adherence to treatment and the resulting pattern of treatment interruptions are key drivers of HIV-1 treatment outcomes. Our model, though largely independent of efficacy data from RCT, was accurate in producing 96-week outcomes, qualitatively and quantitatively comparable to the ones observed in the STaR trial. We demonstrate that multi-paradigm micro-simulation modeling is a promising tool to generate evidence about optimal policy strategies in HIV-1 treatment, including treatment efficacy, HIV-1 transmission, and cost-effectiveness analysis. Public Library of Science 2016-02-12 /pmc/articles/PMC4752501/ /pubmed/26870960 http://dx.doi.org/10.1371/journal.pone.0149007 Text en © 2016 Vandewalle et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Vandewalle, Björn
Llibre, Josep M.
Parienti, Jean-Jacques
Ustianowski, Andrew
Camacho, Ricardo
Smith, Colette
Miners, Alec
Ferreira, Diana
Félix, Jorge
EPICE-HIV: An Epidemiologic Cost-Effectiveness Model for HIV Treatment
title EPICE-HIV: An Epidemiologic Cost-Effectiveness Model for HIV Treatment
title_full EPICE-HIV: An Epidemiologic Cost-Effectiveness Model for HIV Treatment
title_fullStr EPICE-HIV: An Epidemiologic Cost-Effectiveness Model for HIV Treatment
title_full_unstemmed EPICE-HIV: An Epidemiologic Cost-Effectiveness Model for HIV Treatment
title_short EPICE-HIV: An Epidemiologic Cost-Effectiveness Model for HIV Treatment
title_sort epice-hiv: an epidemiologic cost-effectiveness model for hiv treatment
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4752501/
https://www.ncbi.nlm.nih.gov/pubmed/26870960
http://dx.doi.org/10.1371/journal.pone.0149007
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