Volume 61, Issue 3
RESEARCH PAPER

Monitoring futility and efficacy in phase II trials with Bayesian posterior distributions—A calibration approach

Annette Kopp‐Schneider

Corresponding Author

E-mail address: kopp@dkfz.de

Division of Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, Germany

Correspondence

Annette Kopp‐Schneider, Division of Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, Germany.

Email: kopp@dkfz.de

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Manuel Wiesenfarth

Division of Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, Germany

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Ruth Witt

Clinical Trial Center, National Center for Tumor Diseases, Heidelberg, Germany

Hopp Children's Cancer Center at NCT Heidelberg (KiTZ), Department of Pediatric Oncology and Hematology and Clinical Cooperation Unit Pediatric Oncology, University Hospital and German Cancer Research Center (DKFZ), Heidelberg, Germany

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Dominic Edelmann

Division of Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, Germany

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Olaf Witt

Hopp Children's Cancer Center at NCT Heidelberg (KiTZ), Department of Pediatric Oncology and Hematology and Clinical Cooperation Unit Pediatric Oncology, University Hospital and German Cancer Research Center (DKFZ), Heidelberg, Germany

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Ulrich Abel

Clinical Trial Center, National Center for Tumor Diseases, Heidelberg, Germany

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First published: 02 September 2018
Citations: 5

Abstract

A multistage single arm phase II trial with binary endpoint is considered. Bayesian posterior probabilities are used to monitor futility in interim analyses and efficacy in the final analysis. For a beta‐binomial model, decision rules based on Bayesian posterior probabilities are converted to “traditional” decision rules in terms of number of responders among patients observed so far. Analytical derivations are given for the probability of stopping for futility and for the probability to declare efficacy. A workflow is presented on how to select the parameters specifying the Bayesian design, and the operating characteristics of the design are investigated. It is outlined how the presented approach can be transferred to statistical models other than the beta‐binomial model.

Number of times cited according to CrossRef: 5

  • INFORM2 NivEnt: The first trial of the INFORM2 biomarker driven phase I/II trial series: the combination of nivolumab and entinostat in children and adolescents with refractory high-risk malignancies, BMC Cancer, 10.1186/s12885-020-07008-8, 20, 1, (2020).
  • Power gains by using external information in clinical trials are typically not possible when requiring strict type I error control, Biometrical Journal, 10.1002/bimj.201800395, 62, 2, (361-374), (2019).
  • Open fire ovens and effects of in‐home lavash bread baking on carbon monoxide exposure and carboxyhemoglobin levels among women in rural Armenia, Indoor Air, 10.1111/ina.12623, 30, 2, (361-369), (2019).
  • Can germination explain the distribution of tree species in a savanna wetland?, Austral Ecology, 10.1111/aec.12811, 44, 8, (1373-1383), (2019).
  • Competitive effects and responses of the invasive grass Eragrostis plana in Río de la Plata grasslands, Austral Ecology, 10.1111/aec.12822, 44, 8, (1478-1486), (2019).

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