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A product of independent beta probabilities dose escalation design for dual-agent phase I trials

Mander, Adrian P. and Sweeting, Michael J. 2015. A product of independent beta probabilities dose escalation design for dual-agent phase I trials. Statistics in Medicine 34 (8) , 1261--1276. 10.1002/sim.6434

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Dual‐agent trials are now increasingly common in oncology research, and many proposed dose‐escalation designs are available in the statistical literature. Despite this, the translation from statistical design to practical application is slow, as has been highlighted in single‐agent phase I trials, where a 3 + 3 rule‐based design is often still used. To expedite this process, new dose‐escalation designs need to be not only scientifically beneficial but also easy to understand and implement by clinicians. In this paper, we propose a curve‐free (nonparametric) design for a dual‐agent trial in which the model parameters are the probabilities of toxicity at each of the dose combinations. We show that it is relatively trivial for a clinician's prior beliefs or historical information to be incorporated in the model and updating is fast and computationally simple through the use of conjugate Bayesian inference. Monotonicity is ensured by considering only a set of monotonic contours for the distribution of the maximum tolerated contour, which defines the dose‐escalation decision process. Varied experimentation around the contour is achievable, and multiple dose combinations can be recommended to take forward to phase II. Code for R, Stata and Excel are available for implementation.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Medicine
Centre for Trials Research (CNTRR)
Publisher: Wiley
ISSN: 0277-6715
Date of First Compliant Deposit: 12 June 2019
Last Modified: 12 Jun 2019 11:01

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