Design of Long-Term Viral Dynamic Studies in Semiparametric Mixed-Effects Models

• Activity Number: 284
• Type: Contributed
• Date/Time: Tuesday, July 31, 2007 : 10:30 AM to 12:20 PM
• Sponsor: Biometrics Section
• Author(s): Jeong-Gun Park*+ and Yangxin Huang and Yiliang Zhu
• Companies: Harvard School of Public Heath/Frontier Science & Technology Research Foundation and University of South Florida and University of South Florida
• Keywords: HIV dynamics ; Nonlinear mixed-effects Models ; Long-term viral dynamics

Abstract

Studies of HIV dynamics in AIDS research are very important for understanding the pathogenesis of HIV infection and for assessing the potency of antiviral therapies. Nonlinear parametric models, derived from the mechanisms of HIV infection and drug action, have been used to fit short-term clinical data from AIDS clinical trials, but they are not adequate to fit the long-term viral dynamic data. Here we use a simulation-based approach to deal with design problems for long-term longitudinal HIV dynamic studies under the framework of semiparametric nonlinear mixed-effects models which can not only preserve the meaningful interpretation of the short-term HIV dynamics, but can also characterize the long-term viral dynamics. We compare a finite number of feasible candidate designs numerically and provide guidance on how a design might be chosen in practice.