Commensurate Bayesian models for combining current and historical survival information
Bradley P. Carlin, University of Minnesota Brian P Hobbs, University of Texas MD Anderson Cancer Center *Theodore C Lystig, Medtronic, Inc Thomas A Murray, University of Minnesota Keywords: Bayesian hierarchical modeling, Commensurate prior, Safety, Evidence synthesis, Medical devices In this presentation we will consider a commensurate Bayesian model using a piecewise exponential likelihood for synthesizing evidence from two sources of non-exchangeable time-to-event data. After a brief introduction of possible alternative approaches and an overview of the proposed method, we will move on to applying the method in real data. The setting will be a pair of post-market surveillance datasets capturing adverse events from persons on dialysis that underwent cardiac revascularization with a bare metal stent. We will focus on the manner in which the methods allow us to update fairly our current understanding of safety for the medical device as we progressively accumulate new information.
|
Key Dates
-
April 30 - May 22, 2013
Invited Abstract Submission Open -
June 4, 2013
Online Registration Opens -
August 9 - August 23, 2013
Invited Abstract Editing -
August 23, 2013
Short Course materials due from Instructors -
August 26, 2013
Housing Deadline -
September 9, 2013
Cancellation Deadline and Registration Closes @ 11:59 pm EDT -
September 16 - September 18, 2013
Marriott Wardman Park, Washington, DC