Bayesian Group Sequential Clinical Trial Design Using Total Toxicity Burden and Progression-Free Survival

• Activity Number: 16
• Type: Topic Contributed
• Date/Time: Sunday, July 31, 2016 : 2:00 PM to 3:50 PM
• Sponsor: Section on Bayesian Statistical Science
• Author(s): Brian Hobbs* and Peter F. Thall and Steven H. Lin
• Companies: MD Anderson Cancer Center and MD Anderson Cancer Center and MD Anderson Cancer Center
• Keywords: Bayesian analysis ; Co-primary endpoints ; Frailty model ; Prior elicitation ; Sequential design ; Utilities

Abstract

I will describe a Bayesian group sequential clinical trial design, based on total toxicity burden (TTB) and progression-free survival, which is being used to implement a trial for comparing two radiation therapy modalities for esophageal cancer patients undergoing a trimodality regime consisting of chemoradiation ± surgery. Each patient's toxicities are modelled as a multivariate doubly stochastic Poisson point process, with marks identifying toxicity grades. Each grade of each type of toxicity is assigned a severity weight, elicited from clinical oncologists who are familiar with the disease and treatments. TTB is defined as a severity-weighted sum over the different toxicities that may occur up to 12 months from the start of treatment. Latent frailties are used to formulate a multivariate model for all outcomes. Group sequential decision rules are based on posterior mean TTB and progression-free survival time. The statistical model and corresponding trial design offer powerful tools for sequential safety monitoring in settings wherein patients are at risk of many types of toxicities that may result from the combined impacts of multiple types of therapy.