Borrowing Strength with Nonexchangeable Priors Over Subpopulations

• Activity Number: 52
• Type: Invited
• Date/Time: Sunday, July 31, 2011 : 4:00 PM to 5:50 PM
• Sponsor: Section on Nonparametric Statistics
• Author(s): Fernando Quintana*+ and Luis León-Novelo and B. Nebiyou Bekele and Peter Mueller
• Companies: Pontificia Universidad Católica de Chile and University of Florida and The University of Texas MD Anderson Cancer Center and The University of Texas MD Anderson Cancer Center
• Keywords: Binary data ; Clinical trial ; Nonexchangeable ; Nonparametric Bayes

Abstract

We introduce a non-parametric Bayesian model for a phase II clinical trial with patients presenting different subtypes of the disease under study. We consider the case when small sample sizes require extensive borrowing of information across subtypes, but the subtypes are not a priori exchangeable. We introduce a random partition model for the set of disease subtypes. All subtypes within the same cluster share a common success probability. The random partition model is a variation of the product partition model with a non-exchangeable prior structure. The data come from a clinical trial of patients with sarcoma. Each patient presents one subtype of the disease and subtypes are grouped by good, intermediate and poor prognosis. Two subtypes with equal prognosis should be more likely a priori to co-cluster than those with different prognosis. When assessing the success rate for a particular