title: Design of long-term HIV dynamic studies using semiparametric mixed-effects models.
abstract: Studies of HIV dynamics in AIDS research are very important in understanding the pathogenesis of HIV-1 infection and also in assessing the effectiveness of antiviral therapies. There are many AIDS clinical trials on HIV dynamics currently in development worldwide, giving rise to many design issues yet to be addressed. For example, most studies are focused on short-term viral dynamics and the existing models may not be applicable to describe long-term virologic response. In this paper, we use a simulation-based approach to study the designs of long-term viral dynamics under semiparametric nonlinear mixed-effects models. These models not only can preserve the meaningful interpretation of the short-term HIV dynamics, but also characterize the long-term virologic responses to antiretroviral (ARV) treatment. We investigate a number of feasible clinical protocol designs similar to those currently used in AIDS clinical trials. In particular, we evaluate whether earlier samplings can result in more useful information about the viral response trajectory; we also evaluate the effectiveness of two strategies: more frequent samplings per subject with fewer subjects versus fewer samplings per subject with more subjects while keeping the total number of samplings constant. The results of our investigation provide quantitative guidance for designing and selecting ARV therapy.
authors.affiliation: Department of Epidemiology & 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: Jeong-Gun
authors.initials: JG
authors.lastname: Park
authors.forename: Yiliang
authors.initials: Y
authors.lastname: Zhu
mesh_terms: D000465:Algorithms; D002986:Clinical Trials as Topic / Q000379:methods* / Q000706:statistics & numerical data; D003198:Computer Simulation; D015658:HIV Infections / Q000097:blood / Q000821:virology*; D006801:Humans; D008954:Models, Biological; D015233:Models, Statistical; D019562:Viral Load