title: Adaptive trial designs.
abstract: We review adaptive designs for clinical trials, giving special attention to the control of the Type I error in late-phase confirmatory trials, when the trial planner wishes to adjust the final sample size of the study in response to an unblinded analysis of interim estimates of treatment effects. We point out that there is considerable inefficiency in using the adaptive designs that employ conditional power calculations to reestimate the sample size and that maintain the Type I error by using certain weighted test statistics. Although these adaptive designs have little advantage over familiar group-sequential designs, our review also describes recent developments in adaptive designs that are both flexible and efficient. We also discuss the use of Bayesian designs, when the context of use demands control over operating characteristics (Type I and II errors) and correction of the bias of estimated treatment effects.
authors.affiliation: Department of Statistics, Stanford University, Stanford, California 94305, USA.
authors.forename: Tze Leung
authors.initials: TL
authors.lastname: Lai
authors.forename: Philip William
authors.initials: PW
authors.lastname: Lavori
authors.forename: Mei-Chiung
authors.initials: MC
authors.lastname: Shih
mesh_terms: D001499:Bayes Theorem; D015982:Bias; D002986:Clinical Trials as Topic; D003627:Data Interpretation, Statistical; D006801:Humans; D015233:Models, Statistical; D012107:Research Design; D018401:Sample Size