title: Adaptive design of confirmatory trials: Advances and challenges.
abstract: The past decade witnessed major developments in innovative designs of confirmatory clinical trials, and adaptive designs represent the most active area of these developments. We give an overview of the developments and associated statistical methods in several classes of adaptive designs of confirmatory trials. We also discuss their statistical difficulties and implementation challenges, and show how these problems are connected to other branches of mainstream Statistics, which we then apply to resolve the difficulties and bypass the bottlenecks in the development of adaptive designs for the next decade.
authors.affiliation: Department of Statistics, Stanford University, Stanford, CA, USA. Electronic address: lait@stanford.edu.
authors.forename: Tze Leung
authors.initials: TL
authors.lastname: Lai
authors.affiliation: Department of Health Research and Policy, Stanford University, Stanford, CA, USA.
authors.forename: Philip W
authors.initials: PW
authors.lastname: Lavori
authors.affiliation: Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA.
authors.forename: Ka Wai
authors.initials: KW
authors.lastname: Tsang
mesh_terms: D001499:Bayes Theorem; D002986:Clinical Trials as Topic / Q000191:economics / Q000379:methods* / Q000592:standards; D017322:Clinical Trials, Phase II as Topic / Q000379:methods; D017326:Clinical Trials, Phase III as Topic / Q000379:methods; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D006801:Humans; D012107:Research Design; D018401:Sample Size; D014481:United States; D014486:United States Food and Drug Administration / Q000592:standards
keywords: Adaptive design; Adaptive randomization; Bayesian inference; Early stopping; Hybrid resampling; Multi-arm bandits