title: Some controversial multiple testing problems in regulatory applications.
abstract: Multiple testing problems in regulatory applications are often more challenging than the problems of handling a set of mathematical symbols representing multiple null hypotheses under testing. In the union-intersection setting, it is important to define a family of null hypotheses relevant to the clinical questions at issue. The distinction between primary endpoint and secondary endpoint needs to be considered properly in different clinical applications. Without proper consideration, the widely used sequential gate keeping strategies often impose too many logical restrictions to make sense, particularly to deal with the problem of testing multiple doses and multiple endpoints, the problem of testing a composite endpoint and its component endpoints, and the problem of testing superiority and noninferiority in the presence of multiple endpoints. Partitioning the null hypotheses involved in closed testing into clinical relevant orderings or sets can be a viable alternative to resolving the illogical problems requiring more attention from clinical trialists in defining the clinical hypotheses or clinical question(s) at the design stage. In the intersection-union setting there is little room for alleviating the stringency of the requirement that each endpoint must meet the same intended alpha level, unless the parameter space under the null hypothesis can be substantially restricted. Such restriction often requires insurmountable justification and usually cannot be supported by the internal data. Thus, a possible remedial approach to alleviate the possible conservatism as a result of this requirement is a group-sequential design strategy that starts with a conservative sample size planning and then utilizes an alpha spending function to possibly reach the conclusion early.
authors.affiliation: Division of Biometrics I, OB/OTS/CDER, FDA, Silver Spring, Maryland 20993-0002, USA. hsienming.hung@fda.hhs.gov
authors.forename: H M James
authors.initials: HM
authors.lastname: Hung
authors.forename: Sue-Jane
authors.initials: SJ
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D017277:Drug Approval; D023381:Endpoint Determination; D006801:Humans; D015233:Models, Statistical; D004364:Pharmaceutical Preparations / Q000008:administration & dosage; D011336:Probability; D012107:Research Design; D018401:Sample Size; D016896:Treatment Outcome; D014481:United States; D014486:United States Food and Drug Administration
chemical_list: D004364:Pharmaceutical Preparations