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Covariate analysis of viral eradication studies
Authors:Cheng D M  Lagakos S W
Institution:Department of Biostatistics, Harvard University School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA. dcheng@hsph.harvard.edu
Abstract:An important issue arising in therapeutic studies of hepatitis C and HIV is the identification of and adjustment for covariates associated with viral eradication and resistance. Analyses of such data are complicated by the fact that eradication is an occult event that is not directly observable, resulting in unique types of censored observations that do not arise in other competing risks settings. This paper proposes a semiparametric regression model to assess the association between multiple covariates and the eradication/resistance processes. The proposed methods are based on a piecewise proportional hazards model that allows parameters to vary between observation times. We illustrate the methods with data from recent hepatitis C clinical trials.
Keywords:Censored observations  Competing risks  Maximum likelihood  Regression
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