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Retrospective analysis of chronic hepatitis C in untreated patients with nonlinear mixed effects model

By Liam Fanning, Orla Crosbie, Elizabeth Kenny-Walsh, Jian Huang, John Levis and Kathleen O’Sullivan

Abstract

It is well known that viral load of the hepatitis C virus (HCV) is related to the efficacy of interferon therapy. The complex biological parameters that impact on viral load are essentially unknown. The current knowledge of the hepatitis C virus does not provide a mathematical model for viral load dynamics within untreated patients. We car-ried out an empirical modelling to investigate whether different fluctuation patterns exist and how these patterns (if exist) are related to host-specific factors. Data was prospectively col-lected from 147 untreated patients chronically infected with hepatitis C, each contributing be-tween 2 to 10 years of measurements. We pro-pose to use a three parameter logistic model to describe the overall pattern of viral load fluctua-tion based on an exploratory analysis of the data. To incorporate the correlation feature of longitu-dinal data and patient to patient variation, we introduced random effects components into the model. On the basis of this nonlinear mixed ef-fects modelling, we investigated effects of host-specific factors on viral load fluctuation by in-corporating covariates into the model. The pro-posed model provided a good fit for describing fluctuations of viral load measured with varying frequency over different time intervals. The aver-age viral load growth time was significantly dif-ferent between infection sources. There was a large patient to patient variation in viral load as-ymptote

Topics: Logistic model, Viral load, Viral genotype, Mixed effects modelling, LCC:Medicine (General), LCC:R5-920, LCC:Medicine, LCC:R, DOAJ:Medicine (General), DOAJ:Health Sciences
Publisher: Scientific Research Publishing
Year: 2008
DOI identifier: 10.4236/jbise.2008.12014
OAI identifier: oai:doaj.org/article:c1672d8cdb084cf09b87d0df2155ddef
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