title: Time-to-event analysis with treatment arm selection at interim.
abstract: This paper discusses the application of an adaptive design for treatment arm selection in an oncology trial, with survival as the primary endpoint and disease progression as a key secondary endpoint. We carried out treatment arm selection at an interim analysis by using Bayesian predictive power combining evidence from the two endpoints. At the final analysis, we carried out a frequentist statistical test of efficacy on the survival endpoint. We investigated several approaches (Bonferroni approach, 'Dunnett-like' approach, a conditional error function approach and a combination p-value approach) with respect to their power and the precise conditions under which type I error control is attained.
authors: Novartis Pharma AG, Basel, Switzerland. lilla.di_scala@novartis.com
authors: L
authors: L
authors: Di Scala
authors: E
authors: E
authors: Glimm
mesh_terms: D001499:Bayes Theorem; D017322:Clinical Trials, Phase II as Topic / Q000706:statistics & numerical data*; D017326:Clinical Trials, Phase III as Topic / Q000706:statistics & numerical data*; D003198:Computer Simulation; D003657:Decision Making; D006801:Humans; D008175:Lung Neoplasms / Q000188:drug therapy*; D015233:Models, Statistical; D058990:Molecular Targeted Therapy / Q000706:statistics & numerical data*; D018579:Patient Selection; D012107:Research Design / Q000706:statistics & numerical data*; D016019:Survival Analysis; D016896:Treatment Outcome