Population HIV-1 dynamics in vivo: applicable models and inferential tools for virological data from AIDS clinical trials

Biometrics
H Wu, A A Ding

Abstract

In this paper, we introduce a novel application of hierarchical nonlinear mixed-effect models to HIV dynamics. We show that a simple model with a sum of exponentials can give a good fit to the observed clinical data of HIV-1 dynamics (HIV-1 RNA copies) after initiation of potent antiviral treatments and can also be justified by a biological compartment model for the interaction between HIV and its host cells. This kind of model enjoys both biological interpretability and mathematical simplicity after reparameterization and simplification. A model simplification procedure is proposed and illustrated through examples. We interpret and justify various simplified models based on clinical data taken during different phases of viral dynamics during antiviral treatments. We suggest the hierarchical nonlinear mixed-effect model approach for parameter estimation and other statistical inferences. In the context of an AIDS clinical trial involving patients treated with a combination of potent antiviral agents, we show how the models may be used to draw biologically relevant interpretations from repeated HIV-1 RNA measurements and demonstrate the potential use of the models in clinical decision-making.

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Citations

Jul 12, 2002·Statistics in Medicine·Anthony P FitzgeraldFlorin Vaida
Nov 19, 2002·Statistics in Medicine·Hulin Wu, Jin-Ting Zhang
Jan 24, 2009·Journal of Mathematical Biology·Robert J Smith, B D Aggarwala
Jan 13, 2006·Journal of Pharmacokinetics and Pharmacodynamics·Chantal Csajka, Davide Verotta
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Mar 31, 2004·Mathematical Biosciences·Hua Liang, Naijun Sha
Mar 28, 2002·Mathematical Biosciences·Davide Verotta, Franziska Schaedeli
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Feb 28, 2014·Genetic Testing and Molecular Biomarkers·Mohammad Yahya AreeshiShafiul Haque
Jun 28, 2005·Journal of Acquired Immune Deficiency Syndromes : JAIDS·Hulin WuJohn G Gerber

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