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Practical guidelines for adaptive seamless phase II/III clinical trials that use Bayesian methods
Author(s) -
Kimani Peter K.,
Glimm Ekkehard,
Maurer Willi,
Hutton Jane L.,
Stallard Nigel
Publication year - 2012
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.5326
Subject(s) - computer science , adaptation (eye) , bayesian probability , adaptive design , clinical trial , machine learning , artificial intelligence , medicine , psychology , pathology , neuroscience
Hommel ( Biometrical Journal ; 45:581–589) proposed a flexible testing procedure for seamless phase II/III clinical trials. Schmidli et al. ( Statistics in Medicine ; 26:4925–4938), Kimani et al. ( Statistics in Medicine ; 28:917–936) and Brannath et al. ( Statistics in Medicine ; 28:1445–1463) exploited the flexible testing of Hommel to propose adaptation in seamless phase II/III clinical trials that incorporate prior knowledge by using Bayesian methods. In this paper, we show that adaptation incorporating prior knowledge may lead to higher power. Other important issues to consider in such adaptive designs are the gain in power (or saving in patients) over traditional testing and how utility values used to make the adaptation may be used to stop a trial early. In contrast to the aforementioned authors, we discuss these issues in detail and propose a unified approach to address them so that implementing the aforementioned designs and proposing similar designs is clearer. Copyright © 2012 John Wiley & Sons, Ltd.