Cancer immunotherapy trial design with random delayed treatment effect and cure rate

Jianrong Wu, Jing Wei

Research output: Contribution to journalArticlepeer-review


Immunotherapies are increasingly used for treating patients with advanced-stage cancers. However, cancer immunotherapy trials often present delayed treatment effects and long-term survivors which result nonproportional hazard models and challenge the immunotherapy trial designs. In this article, we proposed a general random delayed cure rate model for designing cancer immunotherapy trials. A sample size formula is derived for a weighted log-rank test. The accuracy of sample size estimation is assessed and compared with the existing methods via simulation studies. The sensitivities for misspecifying the random delay time are also studied through simulations.

Original languageEnglish
Pages (from-to)786-797
Number of pages12
JournalStatistics in Medicine
Issue number4
StatePublished - Feb 20 2022

Bibliographical note

Funding Information:
We thank the referees for their constructive comments that have led to significant improvements in the article. This research was supported by the Biostatistics and Bioinformatics Shared Resource Facility of the University of Kentucky Markey Cancer Center Support Grant NCI P30CA177558.

Publisher Copyright:
© 2021 John Wiley & Sons Ltd.

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability


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