JSM 2004 - Toronto

Abstract #302219

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Activity Number: 266
Type: Topic Contributed
Date/Time: Tuesday, August 10, 2004 : 2:00 PM to 3:50 PM
Sponsor: Section on Bayesian Statistical Science
Abstract - #302219
Title: Bayesian Analysis of a New Joint Model with Cure Fraction
Author(s): Debajyoti Sinha*+ and Joseph G. Ibrahim and Ming-Hui Chen
Companies: Medical University of South Carolina and University of North Carolina, Chapel Hill and University of Connecticut
Address: , , ,
Keywords: biological markers ; longitudinal data ; cure rate survival model
Abstract:

Vaccine therapies have received a great deal of attentional recently as potential therapies in cancer clinical trials. However, little is currently known about the biological activity of vaccines and that of finding good markers for assessing the efficacy of these vaccines and predicting clinical outcome. The antibody immune measures IgG and IgM have been proposed as potential markers in melanoma clinical trials because of their observed correlation with clinical outcome in pilot studies. To better understand the role of IgG and IgM for a particular vaccine, we must better understand the relationship of clinical outcome to an individuals antibody (IgG or IgM titires) history over time. Gibbs sampling methodology is given for carrying out Bayesian inference. We illustrate our methodology with a recently completed melanoma clinical trials using vaccine.

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