title: A practical guide to Bayesian group sequential designs.
abstract: Bayesian approaches to the monitoring of group sequential designs have two main advantages compared with classical group sequential designs: first, they facilitate implementation of interim success and futility criteria that are tailored to the subsequent decision making, and second, they allow inclusion of prior information on the treatment difference and on the control group. A general class of Bayesian group sequential designs is presented, where multiple criteria based on the posterior distribution can be defined to reflect clinically meaningful decision criteria on whether to stop or continue the trial at the interim analyses. To evaluate the frequentist operating characteristics of these designs, both simulation methods and numerical integration methods are proposed, as implemented in the corresponding R package gsbDesign. Normal approximations are used to allow fast calculation of these characteristics for various endpoints. The practical implementation of the approach is illustrated with several clinical trial examples from different phases of drug development, with various endpoints, and informative priors.
authors.affiliation: Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland.
authors.forename: Thomas
authors.initials: T
authors.lastname: Gsponer
authors.forename: Florian
authors.initials: F
authors.lastname: Gerber
authors.forename: Björn
authors.initials: B
authors.lastname: Bornkamp
authors.forename: David
authors.initials: D
authors.lastname: Ohlssen
authors.forename: Marc
authors.initials: M
authors.lastname: Vandemeulebroecke
authors.forename: Heinz
authors.initials: H
authors.lastname: Schmidli
mesh_terms: D001499:Bayes Theorem; D002986:Clinical Trials as Topic / Q000379:methods*; D003424:Crohn Disease / Q000188:drug therapy; D055808:Drug Discovery; D006801:Humans; D012107:Research Design
keywords: Bayesian inference; adaptive design; group sequential design; gsbDesign; operating characteristics; prior