title: Practical guidelines for adaptive seamless phase II/III clinical trials that use Bayesian methods.
abstract: 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.
authors.affiliation: Warwick Medical School, The University of Warwick, Coventry, CV4 7AL, UK. peter.k-u.kimani@warwick.ac.uk
authors.forename: Peter K
authors.initials: PK
authors.lastname: Kimani
authors.forename: Ekkehard
authors.initials: E
authors.lastname: Glimm
authors.forename: Willi
authors.initials: W
authors.lastname: Maurer
authors.forename: Jane L
authors.initials: JL
authors.lastname: Hutton
authors.forename: Nigel
authors.initials: N
authors.lastname: Stallard
mesh_terms: D001499:Bayes Theorem; D015982:Bias; D001699:Biometry; D017322:Clinical Trials, Phase II as Topic / Q000379:methods / Q000706:statistics & numerical data*; D017326:Clinical Trials, Phase III as Topic / Q000379:methods / Q000706:statistics & numerical data*; D003627:Data Interpretation, Statistical; D004305:Dose-Response Relationship, Drug; D023381:Endpoint Determination; D006801:Humans; D015233:Models, Statistical; D012372:ROC Curve; D012107:Research Design / Q000706:statistics & numerical data; D018401:Sample Size