title: Statistical methods for HIV dynamic studies in AIDS clinical trials.
abstract: Studies of HIV dynamics in AIDS research are very important for understanding pathogenesis of HIV infection and for assessing the potency of antiviral therapies. Since the viral dynamic results from clinical data were first published by Ho et al. and Wei et al., the study of HIV-1 dynamics in vivo has drawn a great attention from AIDS clinicians and researchers. Although the important findings from HIV dynamic studies have been published in many prestigious scientific journals, statistical methods for estimating viral dynamic parameters have not been paid enough attention by HIV dynamic investigators. The estimation methods in many viral dynamic studies are very crude and inefficient. In this paper, we review the statistical methods and mathematical models for HIV dynamic data analysis developed in recent years. We also address some practical issues and share our experiences in the design and analysis of viral dynamic studies. Some principles and guidelines for the design and analysis of viral dynamic studies are provided. The methodologies reviewed in this paper are also applicable to studies of other viruses such as hepatitis B virus or hepatitis C virus. We also pose some challenging statistical problems in this area in order to stimulate further study by the statistical research community.
authors.affiliation: Department of Biostatistics and Computational Biology, University of Rochester, School of Medicine and Dentistry, Rochester, NY 14642, USA. hwu@bst.rochester.edu
authors.forename: Hulin
authors.initials: H
authors.lastname: Wu
mesh_terms: D000163:Acquired Immunodeficiency Syndrome / Q000188:drug therapy / Q000821:virology*; D023241:Antiretroviral Therapy, Highly Active; D001499:Bayes Theorem; D001699:Biometry; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data; D015658:HIV Infections / Q000188:drug therapy / Q000821:virology; D015497:HIV-1 / Q000302:isolation & purification*; D006801:Humans; D016018:Least-Squares Analysis; D015233:Models, Statistical; D017711:Nonlinear Dynamics; D012367:RNA, Viral / Q000032:analysis
chemical_list: D012367:RNA, Viral