Bayesian Enrichment Strategies for Randomized Discontinuation Trials
Article first published online: 29 JUN 2011
© 2011, The International Biometric Society
Volume 68, Issue 1, pages 203–211, March 2012
How to Cite
Trippa, L., Rosner, G. L. and Müller, P. (2012), Bayesian Enrichment Strategies for Randomized Discontinuation Trials. Biometrics, 68: 203–211. doi: 10.1111/j.1541-0420.2011.01623.x
- Issue published online: 23 MAR 2012
- Article first published online: 29 JUN 2011
- Received April 2009. Revised August 2010. Accepted September 2010.
- Clinical trials;
- Enrichment designs;
- Randomized discontinuation design;
- Tumor growth models
Summary We propose optimal choice of the design parameters for random discontinuation designs (RDD) using a Bayesian decision-theoretic approach. We consider applications of RDDs to oncology phase II studies evaluating activity of cytostatic agents. The design consists of two stages. The preliminary open-label stage treats all patients with the new agent and identifies a possibly sensitive subpopulation. The subsequent second stage randomizes, treats, follows, and compares outcomes among patients in the identified subgroup, with randomization to either the new or a control treatment. Several tuning parameters characterize the design: the number of patients in the trial, the duration of the preliminary stage, and the duration of follow-up after randomization. We define a probability model for tumor growth, specify a suitable utility function, and develop a computational procedure for selecting the optimal tuning parameters.