A Bayesian model‐free approach to combination therapy phase I trials using censored time‐to‐toxicity data
File(s)rssc.12323.pdf (1.04 MB)
Published version
Author(s)
Wheeler, Graham M
Sweeting, Michael J
Mander, Adrian P
Type
Journal Article
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.
Date Issued
2019-02
Date Acceptance
2018-10-02
Citation
Journal of the Royal Statistical Society: Series C (Applied Statistics), 2019, 68 (2), pp.309-329
ISSN
0035-9254
Publisher
Wiley
Start Page
309
End Page
329
Journal / Book Title
Journal of the Royal Statistical Society: Series C (Applied Statistics)
Volume
68
Issue
2
Copyright Statement
© 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.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
License URL
Identifier
https://rss.onlinelibrary.wiley.com/doi/full/10.1111/rssc.12323
Subjects
Statistics & Probability
0104 Statistics
Publication Status
Published
Date Publish Online
2018-11-22