Bayesian Enrollment Timeline Projection

• Activity Number: 595
• Type: Topic Contributed
• Date/Time: Thursday, August 7, 2014 : 8:30 AM to 10:20 AM
• Sponsor: Korean International Statistical Society
• Author(s): Anthiyur Kannappan*+ and Suresh Ankolekar and Nitin Patel and Pralay Senchaudhuri
• Companies: Cytel and Maastricht School of Management and Cytel and Cytel
• Keywords: Clinical trial enrollment timeline ; Poisson-Gamma model ; Bayesian updates ; milestone prediction

Abstract

The accuracy of enrollment timeline projection plays an important role in planning and execution of clinical trial operations. This is particularly critical in time to event trials, where accuracy of event timeline projection is contingent on corresponding enrollment prediction. This talk will discuss a simulation approach for enrollment timeline projection using Bayesian Poisson-Gamma model in two real-life multi-center oncology trials. The model parameters include site structure of a typical clinical trial in terms of countries, sites, activation plan, and enrollment rates/caps at country/site level. The prior shape and scale parameters for Gamma distribution are estimated on the basis of the specified enrollment rates. During the trial, all available information on observed enrollments and site activations is progressively used for Bayesian updates of the Gamma parameters. The model has been validated using past data from several real-life clinical trials. In addition to the enrollment timeline projection in terms of 95% credible intervals and other specified percentiles of interest, the model also generates probability distributions of reaching specific enrollment milestones.