TITLE:
Retrospective analysis of chronic hepatitis C in untreated patients with nonlinear mixed effects model
AUTHORS:
Jian Huang, Kathleen O’Sullivan, John Levis, Elizabeth Kenny-Walsh, Orla Crosbie, Liam Fanning
KEYWORDS:
Logistic model, Viral load, Viral genotype, Mixed effects modelling
JOURNAL NAME:
Journal of Biomedical Science and Engineering,
Vol.1 No.2,
August
25,
2008
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.