title: Discussion of the article by Trippa, Rosner, and Müller on Bayesian enrichment strategies for randomized discontinuation trials.
abstract: We congratulate Trippa, Rosner, and Müller (2011, Biometrics, in press) on an intriguing and timely article. The randomized discontinuation design (RDD) has only recently been used in cancer clinical trials, and methodological understanding on how to best design such studies is limited. The authors’ approach to optimize RDD designs based on prior information and utility considerations is an important step forward. A noteworthy element is their use of a semimechanistic model to describe tumor growth. Mathematical models have provided considerable insight on the complex process of tumor evolution (Preziosi, 2003, Cancer Modelling and Simulation). Utilizing this knowledge should lead to better design, analysis, and decisions.
authors.affiliation: Statistical Methodology, Development, Novartis Pharma AG, Basel, Switzerland. heinz.schmidli@novartis.com
authors.forename: Heinz
authors.initials: H
authors.lastname: Schmidli
authors.forename: Beat
authors.initials: B
authors.lastname: Neuenschwander
mesh_terms: D001499:Bayes Theorem; D001699:Biometry / Q000379:methods*; D003627:Data Interpretation, Statistical; D006801:Humans; D015233:Models, Statistical; D009369:Neoplasms / Q000453:epidemiology*; D016032:Randomized Controlled Trials as Topic / Q000379:methods* / Q000706:statistics & numerical data*