Cancer immunotherapy trial design with cure rate and delayed treatment effect

Jing Wei, Jianrong Wu

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Cancer immunotherapy trials have two special features: a delayed treatment effect and a cure rate. Both features violate the proportional hazard model assumption and ignoring either one of the two features in an immunotherapy trial design will result in substantial loss of statistical power. To properly design immunotherapy trials, we proposed a piecewise proportional hazard cure rate model to incorporate both delayed treatment effect and cure rate into the trial design consideration. A sample size formula is derived for a weighted log-rank test under a fixed alternative hypothesis. The accuracy of sample size calculation using the new formula is assessed and compared with the existing methods via simulation studies. A real immunotherapy trial is used to illustrate the study design along with practical consideration of balance between sample size and follow-up time.

Original languageEnglish
Pages (from-to)698-708
Number of pages11
JournalStatistics in Medicine
Volume39
Issue number6
DOIs
StatePublished - Mar 15 2020

Bibliographical note

Publisher Copyright:
© 2019 John Wiley & Sons, Ltd.

Keywords

  • cure rate
  • delayed treatment effect
  • piecewise proportional hazards model
  • sample size
  • weighted log-rank test

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability

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