Adherence to antiretroviral therapy,virological response,and time to resistance in the Dakar cohort |
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Authors: | M. Tournoud J. F. Etard R. Ecochard V. DeGruttola |
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Affiliation: | 1. Department of Biostatistics, Harvard School of Public Health, MA, U.S.A.;2. Institut de Recherche pour le Développement, Université Montpellier I, UMR 145, Montpellier, France;3. Service de Biostatistiques, Hospices Civils de Lyon, Lyon, France;4. Université de Lyon, Université Lyon 1, UMR CNRS 5558, Laboratoire Biostatistique‐Santé, Lyon, France |
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Abstract: | ![]() In 1998, with the launch of the Senegalese Initiative for Antiretroviral Access (ISAARV), Senegal became one of the first African countries to propose an antiretroviral access program. Our objective in this paper is to study the time to any first drug resistance, as well as predictors of the time to resistance. We propose a joint model to study the effect of adherence to the HAART therapy, and virological response on the time to resistance mutations. A logistic mixed model is used to model the time‐dependent adherence process; and a Markov model is used to study the virological response. Given the presence of missing data in the adherence process and in the virological response, the latent adherence and virological states are then included in the linear predictor of the time to resistance model. The proposed time to resistance model takes into account interval‐censored data as well as null hazard periods, during which the viral replication is very low. A Bayesian approach is used for accommodating with missing data and for prediction. We also propose model checking tools to study model adequacy. Copyright © 2009 John Wiley & Sons, Ltd. |
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Keywords: | joint models virological failure adherence to antiretroviral therapy resistance mutations Bayesian prediction |
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