Multipopulation Tailoring Clinical Trials: Design, Analysis, and Inference Considerations

Brian A. Millen, Alex Dmitrienko, Sumithra J. Mandrekar, Zongjun Zhang, Dominique Williams

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

Several recent publications have focused on statistical considerations that arise in multipopulation tailoring clinical trials that evaluate treatment effect in an overall patient population as well as one or more predefined subpopulations. This paper presents a decision-making framework applicable to these trials and evaluates the operating characteristics of this framework versus one based solely on the results of primary hypothesis tests. The operating characteristics are presented as rates of applicable errors, known as influence errors and interaction errors.

Original languageEnglish (US)
Pages (from-to)453-462
Number of pages10
JournalTherapeutic Innovation and Regulatory Science
Volume48
Issue number4
DOIs
StatePublished - Jul 2014

Keywords

  • familywise error rate
  • influence condition
  • interaction condition
  • subgroup analysis
  • tailored therapeutics

ASJC Scopus subject areas

  • Pharmacology, Toxicology and Pharmaceutics (miscellaneous)
  • Public Health, Environmental and Occupational Health
  • Pharmacology (medical)

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