Literature DB >> 17715162

Segmental modeling of changing viral load to assess drug resistance in HIV infection.

H Liang1.   

Abstract

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.

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Year:  2007        PMID: 17715162      PMCID: PMC2824144          DOI: 10.1177/0962280206071850

Source DB:  PubMed          Journal:  Stat Methods Med Res        ISSN: 0962-2802            Impact factor:   3.021


  11 in total

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

Authors:  H Wu; A A Ding
Journal:  Biometrics       Date:  1999-06       Impact factor: 2.571

2.  Nonlinear mixed effects models for repeated measures data.

Authors:  M L Lindstrom; D M Bates
Journal:  Biometrics       Date:  1990-09       Impact factor: 2.571

3.  Decay characteristics of HIV-1-infected compartments during combination therapy.

Authors:  A S Perelson; P Essunger; Y Cao; M Vesanen; A Hurley; K Saksela; M Markowitz; D D Ho
Journal:  Nature       Date:  1997-05-08       Impact factor: 49.962

4.  HIV-1 dynamics in vivo: virion clearance rate, infected cell life-span, and viral generation time.

Authors:  A S Perelson; A U Neumann; M Markowitz; J M Leonard; D D Ho
Journal:  Science       Date:  1996-03-15       Impact factor: 47.728

5.  Correlation between reduction in plasma HIV-1 RNA concentration 1 week after start of antiretroviral treatment and longer-term efficacy.

Authors:  M A Polis; I A Sidorov; C Yoder; S Jankelevich; J Metcalf; B U Mueller; M A Dimitrov; P Pizzo; R Yarchoan; D S Dimitrov
Journal:  Lancet       Date:  2001-11-24       Impact factor: 79.321

6.  Relationships between antiviral treatment effects and biphasic viral decay rates in modeling HIV dynamics.

Authors:  A A Ding; H Wu
Journal:  Math Biosci       Date:  1999-08       Impact factor: 2.144

7.  Characterization of viral dynamics in human immunodeficiency virus type 1-infected patients treated with combination antiretroviral therapy: relationships to host factors, cellular restoration, and virologic end points.

Authors:  H Wu; D R Kuritzkes; D R McClernon; H Kessler; E Connick; A Landay; G Spear; M Heath-Chiozzi; F Rousseau; L Fox; J Spritzler; J M Leonard; M M Lederman
Journal:  J Infect Dis       Date:  1999-04       Impact factor: 5.226

8.  Rate of HIV-1 decline following antiretroviral therapy is related to viral load at baseline and drug regimen.

Authors:  D W Notermans; J Goudsmit; S A Danner; F de Wolf; A S Perelson; J Mittler
Journal:  AIDS       Date:  1998-08-20       Impact factor: 4.177

9.  Immunologic responses associated with 12 weeks of combination antiretroviral therapy consisting of zidovudine, lamivudine, and ritonavir: results of AIDS Clinical Trials Group Protocol 315.

Authors:  M M Lederman; E Connick; A Landay; D R Kuritzkes; J Spritzler; M St Clair; B L Kotzin; L Fox; M H Chiozzi; J M Leonard; F Rousseau; M Wade; J D Roe; A Martinez; H Kessler
Journal:  J Infect Dis       Date:  1998-07       Impact factor: 5.226

10.  Viral dynamics in human immunodeficiency virus type 1 infection.

Authors:  X Wei; S K Ghosh; M E Taylor; V A Johnson; E A Emini; P Deutsch; J D Lifson; S Bonhoeffer; M A Nowak; B H Hahn
Journal:  Nature       Date:  1995-01-12       Impact factor: 49.962

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