Discussion of the article by Trippa, Rosner, and Müller on Bayesian enrichment strategies for randomized discontinuation trials
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Updated: May 31, 2026

The Adjuvant Efficacy of Angong Niuhuang Pill in the Treatment of Viral Encephalitis: A Meta-Analysis of Randomized Controlled Trials
Published on: April 19, 2024
Heinz Schmidli1, Beat Neuenschwander
1Statistical Methodology, Development, Novartis Pharma AG, Basel, Switzerland. heinz.schmidli@novartis.com
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.
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