A Bayesian model-free approach to combination therapy phase I trials using censored time-to-toxicity data

Graham M. Wheeler*, Michael J. Sweeting, Adrian P. Mander

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

The product of independent beta probabilities escalation design for dual agent phase I dose escalation trials is a Bayesian model-free approach for identifying multiple maximum tolerated dose combinations of novel combination therapies. Despite only being published in 2015, the design has been implemented in at least two oncology trials. However, these trials require patients to have completed follow-up before clinicians can make dose escalation decisions. For trials of radiotherapy or advanced therapeutics, this may lead to impractically long trial durations due to late-onset treatment-related toxicities. We extend the product of independent probabilities escalation design to use censored time-to-event toxicity outcomes for making dose escalation decisions. We show via comprehensive simulation studies and sensitivity analyses that trial duration can be reduced by up to 35%, particularly when recruitment is faster than expected, without compromising on other operating characteristics.

Original languageEnglish
Pages (from-to)309-329
Number of pages21
JournalJournal of the Royal Statistical Society. Series C: Applied Statistics
Volume68
Issue number2
DOIs
Publication statusPublished - 1 Feb 2019
Externally publishedYes

Bibliographical note

Funding Information:
The authors thank the Joint Editor and two reviewers for their insightful comments that have helped to improve this manuscript. A. P. Mander is supported by the UK Medical Research Council (grant G0800860). Additional support for this project for work done at the University of Cambridge came from the UK Medical Research Council (grant MR/L003120/1), the British Heart Foundation (grant RG/13/13/30194) and the UK National Institute for Health Research (Cambridge Biomedical Research Centre). G. M. Wheeler is supported by Cancer Research UK.

Publisher Copyright:
© 2018 The Authors Journal of the Royal Statistical Society: Series C (Applied Statistics) Published by John Wiley & Sons Ltd on behalf of the Royal Statistical Society.

Keywords

  • Adaptive designs
  • Bayesian methods
  • Clinical trials
  • Dose escalation
  • Model-free approach
  • Time to event

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