Segmental modeling of changing viral load to assess drug resistance in HIV infection.
Studies of viral dynamics are important to our understanding of the pathogenesis of HIV-1 infection and in assessment of the potency of antiretroviral therapies. Although many different viral dynamic models and methods for estimating viral dynamic parameters have been proposed and used in various studies, none has been entirely satisfactory. We propose here a segmental model to describe the viral load, and estimate the dynamic parameters by using a mixed-effects model. We address the relation between the baseline viral load and the decay rate of the first phase of viral load decay, and divide patients into three categories on the basis of their changing viral load patterns.
Liang
H
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Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY 14642, USA.
D024882:Drug Resistance, Viral / Q000502:physiology*; D015658:HIV Infections / Q000378:metabolism / Q000821:virology*; D006801:Humans; D016014:Linear Models; D008954:Models, Biological; D012367:RNA, Viral / Q000378:metabolism; D019562:Viral Load / Q000706:statistics & numerical data*
D012367:RNA, Viral
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