The use of local and nonlocal priors in Bayesian test-based monitoring for single-arm phase II clinical trials

Yanhong Zhou, Ruitao Lin, J. Jack Lee

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Bayesian sequential monitoring is widely used in adaptive phase II studies where the objective is to examine whether an experimental drug is efficacious. Common approaches for Bayesian sequential monitoring are based on posterior or predictive probabilities and Bayesian hypothesis testing procedures using Bayes factors. In the first part of the paper, we briefly show the connections between test-based (TB) and posterior probability-based (PB) sequential monitoring approaches. Next, we extensively investigate the choice of local and nonlocal priors for the TB monitoring procedure. We describe the pros and cons of different priors in terms of operating characteristics. We also develop a user-friendly Shiny application to implement the TB design.

Original languageEnglish (US)
Pages (from-to)1183-1199
Number of pages17
JournalPharmaceutical statistics
Volume20
Issue number6
DOIs
StatePublished - Nov 1 2021

Keywords

  • Bayes factor
  • local prior
  • nonlocal prior
  • phase II
  • sequential monitoring

ASJC Scopus subject areas

  • Statistics and Probability
  • Pharmacology
  • Pharmacology (medical)

MD Anderson CCSG core facilities

  • Biostatistics Resource Group

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