Statistical methods for HIV dynamic studies in AIDS clinical trials

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 h...

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Vydáno v:Statistical methods in medical research Ročník 14; číslo 2; s. 171 - 192
Hlavní autor: Wu, Hulin
Médium: Journal Article
Jazyk:angličtina
Vydáno: Thousand Oaks, CA SAGE Publications 01.04.2005
Sage Publications Ltd
Témata:
Acquired immune deficiency syndrome
Acquired Immunodeficiency Syndrome - drug therapy
Acquired Immunodeficiency Syndrome - virology
AIDS
Analysis
Antiretroviral Therapy, Highly Active
Antiviral drugs
Attention
Bayes Theorem
Biometry
Blood diseases
Clinical research
Clinical trials
Clinical Trials as Topic - statistics & numerical data
Community research
Data analysis
Estimation
Hepatitis
Hepatitis B
Hepatitis B virus
Hepatitis C
Hepatitis C virus
HIV
HIV Infections - drug therapy
HIV Infections - virology
HIV-1 - isolation & purification
Human immunodeficiency virus
Human immunodeficiency virus 1
Humans
Infections
Least-Squares Analysis
Mathematical models
Models, Statistical
Nonlinear Dynamics
RNA, Viral - analysis
Statistical analysis
Statistical methods
Statistics
Therapy
ISSN:0962-2802, 1477-0334
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Shrnutí: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.
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ISSN:0962-2802
1477-0334
DOI:10.1191/0962280205sm390oa