Bayesian single-arm phase II trial designs with time-to-event endpoints

Jianrong Wu, Haitao Pan, Chia Wei Hsu

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

For the cancer clinical trials with immunotherapy and molecularly targeted therapy, time-to-event endpoint is often a desired endpoint. In this paper, we present an event-driven approach for Bayesian one-stage and two-stage single-arm phase II trial designs. Two versions of Bayesian one-stage designs were proposed with executable algorithms and meanwhile, we also develop theoretical relationships between the frequentist and Bayesian designs. These findings help investigators who want to design a trial using Bayesian approach have an explicit understanding of how the frequentist properties can be achieved. Moreover, the proposed Bayesian designs using the exact posterior distributions accommodate the single-arm phase II trials with small sample sizes. We also proposed an optimal two-stage approach, which can be regarded as an extension of Simon's two-stage design with the time-to-event endpoint. Comprehensive simulations were conducted to explore the frequentist properties of the proposed Bayesian designs and an R package BayesDesign can be assessed via R CRAN for convenient use of the proposed methods.

Original languageEnglish
Pages (from-to)1235-1248
Number of pages14
JournalPharmaceutical Statistics
Volume20
Issue number6
DOIs
StatePublished - Nov 1 2021

Bibliographical note

Publisher Copyright:
© 2021 John Wiley & Sons Ltd.

Keywords

  • Bayesian design
  • phase II trial
  • proportional hazards
  • sample size calculation
  • time-to-event endpoint

ASJC Scopus subject areas

  • Statistics and Probability
  • Pharmacology
  • Pharmacology (medical)

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