Statistics and Data Science Seminar
Professor Sanjib Basu
Northern Illinois University, Division of Statistics
Bayesian competing risks analysis of cancer survival data from the SEER program
Abstract: The rates of cancers, including age-adjusted mortality and incidence rates,
depict a general increase over the last 30 years. These led some to
question the success of the war on cancer. The rates of many other
competing diseases, on the other hand, have declined. It has been
hypothesized that this decline is somewhat responsible for the rise in
cancer rates. We consider competing risks analysis of cancer survival data
that considers the simultaneous risks of cancer as well as other causes. The
cure rate survival models for cancer postulates a fraction of the patients to be
cured from cancer. We propose a model that incorporates competing risks and, at
the same time, allows a fraction of patients to be cured. We describe Bayesian
analysis of this model, discuss both conceptual and methodological issues
related to model building and model selection, and consider application in
survival data for breast and prostate cancer patients in the SEER registries of
the National Cancer Institute (NCI).
Wednesday November 15, 2006 at 3:30 PM in SEO 512