title: Hierarchical Bayesian inference for HIV dynamic differential equation models incorporating multiple treatment factors.
abstract: Studies on HIV dynamics in AIDS research are very important in understanding the pathogenesis of HIV-1 infection and also in assessing the effectiveness of antiretroviral (ARV) treatment. Viral dynamic models can be formulated through a system of nonlinear ordinary differential equations (ODE), but there has been only limited development of statistical methodologies for inference. This article, motivated by an AIDS clinical study, discusses a hierarchical Bayesian nonlinear mixed-effects modeling approach to dynamic ODE models without a closed-form solution. In this model, we fully integrate viral load, medication adherence, drug resistance, pharmacokinetics, baseline covariates and time-dependent drug efficacy into the data analysis for characterizing long-term virologic responses. Our method is implemented by a data set from an AIDS clinical study. The results suggest that modeling HIV dynamics and virologic responses with consideration of time-varying clinical factors as well as baseline characteristics may be important for HIV/AIDS studies in providing quantitative guidance to better understand the virologic responses to ARV treatment and to help the evaluation of clinical trial design in response to existing therapies.
authors.affiliation: Department of Epidemiology and Biostatistics, College of Public Health, MDC 56, University of South Florida, Tampa, FL 33612, USA. yhuang@health.usf.edu
authors.forename: Yangxin
authors.initials: Y
authors.lastname: Huang
authors.forename: Hulin
authors.initials: H
authors.lastname: Wu
authors.forename: Edward P
authors.initials: EP
authors.lastname: Acosta
mesh_terms: D000163:Acquired Immunodeficiency Syndrome / Q000188:drug therapy* / Q000821:virology*; D019380:Anti-HIV Agents / Q000493:pharmacokinetics / Q000494:pharmacology / Q000627:therapeutic use; D001499:Bayes Theorem; D002986:Clinical Trials as Topic; D006678:HIV / Q000187:drug effects* / Q000502:physiology*; D006801:Humans; D015233:Models, Statistical; D017711:Nonlinear Dynamics; D019562:Viral Load / Q000187:drug effects
chemical_list: D019380:Anti-HIV Agents