Literature DB >> 10783809

A comparison study of models and fitting procedures for biphasic viral dynamics in HIV-1 infected patients treated with antiviral therapies.

A A Ding1, H Wu.   

Abstract

The study of HIV dynamics is one of the most important developments in recent AIDS research. It has led to a new understanding of the pathogenesis of HIV infection. But, although important findings in HIV dynamics have been published in prestigious scientific journals in the last 5 years, the model-fitting procedures used in these publications have not been studied in any detail. In this paper, we evaluate the performance of four model-fitting procedures proposed and used in biphasic HIV dynamic data analysis via extensive Monte Carlo simulations. We propose some guidelines for practitioners to select an appropriate method for their own data analysis. Real data examples from an AIDS clinical trial are provided as illustrations.

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Year:  2000        PMID: 10783809     DOI: 10.1111/j.0006-341x.2000.00293.x

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  7 in total

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Authors:  Chantal Csajka; Davide Verotta
Journal:  J Pharmacokinet Pharmacodyn       Date:  2006-01-11       Impact factor: 2.745

2.  A Bayesian Approach in Differential Equation Dynamic Models Incorporating Clinical Factors and Covariates.

Authors:  Yangxin Huang
Journal:  J Appl Stat       Date:  2010-02-01       Impact factor: 1.404

3.  Initial viral decay to assess the relative antiretroviral potency of protease inhibitor-sparing, nonnucleoside reverse transcriptase inhibitor-sparing, and nucleoside reverse transcriptase inhibitor-sparing regimens for first-line therapy of HIV infection.

Authors:  Richard H Haubrich; Sharon A Riddler; Heather Ribaudo; Gregory Direnzo; Karin L Klingman; Kevin W Garren; David L Butcher; James F Rooney; Diane V Havlir; John W Mellors
Journal:  AIDS       Date:  2011-11-28       Impact factor: 4.177

4.  A non-linear mixed effect dynamic model incorporating prior exposure and adherence to treatment to describe long-term therapy outcome in HIV-patients.

Authors:  Line Labbé; Davide Verotta
Journal:  J Pharmacokinet Pharmacodyn       Date:  2006-06-20       Impact factor: 2.745

5.  Hierarchical Bayesian inference for HIV dynamic differential equation models incorporating multiple treatment factors.

Authors:  Yangxin Huang; Hulin Wu; Edward P Acosta
Journal:  Biom J       Date:  2010-08       Impact factor: 2.207

6.  Rapid human immunodeficiency virus decay in highly active antiretroviral therapy (HAART)-experienced children after starting mega-HAART.

Authors:  Nottasorn Plipat; Ping K Ruan; Terence Fenton; Ram Yogev
Journal:  J Virol       Date:  2004-10       Impact factor: 5.103

Review 7.  Modeling antiretroviral drug responses for HIV-1 infected patients using differential equation models.

Authors:  Yanni Xiao; Hongyu Miao; Sanyi Tang; Hulin Wu
Journal:  Adv Drug Deliv Rev       Date:  2013-04-17       Impact factor: 15.470

  7 in total

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