A utility-based design for randomized comparative trials with ordinal outcomes and prognostic subgroups

Thomas A. Murray, Ying Yuan, Peter F. Thall, Joan H. Elizondo, Wayne L. Hofstetter

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

A design is proposed for randomized comparative trials with ordinal outcomes and prognostic subgroups. The design accounts for patient heterogeneity by allowing possibly different comparative conclusions within subgroups. The comparative testing criterion is based on utilities for the levels of the ordinal outcome and a Bayesian probability model. Designs based on two alternative models that include treatment-subgroup interactions are considered, the proportional odds model and a non-proportional odds model with a hierarchical prior that shrinks toward the proportional odds model. A third design that assumes homogeneity and ignores possible treatment-subgroup interactions also is considered. The three approaches are applied to construct group sequential designs for a trial of nutritional prehabilitation versus standard of care for esophageal cancer patients undergoing chemoradiation and surgery, including both untreated patients and salvage patients whose disease has recurred following previous therapy. A simulation study is presented that compares the three designs, including evaluation of within-subgroup type I and II error probabilities under a variety of scenarios including different combinations of treatment-subgroup interactions.

Original languageEnglish (US)
Pages (from-to)1095-1103
Number of pages9
JournalBiometrics
Volume74
Issue number3
DOIs
StatePublished - Sep 2018

Bibliographical note

Funding Information:
Peter F. Thall was funded in part by NIH/NCI Grant 5-R01-CA083932

Keywords

  • Group sequential
  • Hierarchical model
  • Non-proportional odds
  • Ordinal response
  • Precision medicine

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