Toxicity-dependent feasibility bounds for the escalation with overdose control approach in phase I cancer trials
Author(s)
Wheeler, Graham M
Sweeting, Michael J
Mander, Adrian P
Type
Journal Article
Abstract
Phase I trials of anti-cancer therapies aim to identify a maximum tolerated dose (MTD), defined as the dose that causes unacceptable toxicity in a target proportion of patients. Both rule-based and model-based methods have been proposed for MTD recommendation. The escalation with overdose control (EWOC) approach is a model-based design where the dose assigned to the next patient is one that, given all available data, has a posterior probability of exceeding the MTD equal to a pre-specified value known as the feasibility bound. The aim is to conservatively dose-escalate and approach the MTD, avoiding severe overdosing early on in a trial. The EWOC approach has been applied in practice with the feasibility bound either fixed or varying throughout a trial, yet some of the methods may recommend incoherent dose-escalation, that is, an increase in dose after observing severe toxicity at the current dose. We present examples where varying feasibility bounds have been used in practice, and propose a toxicity-dependent feasibility bound approach that guarantees coherent dose-escalation and incorporates the desirable features of other EWOC approaches. We show via detailed simulation studies that the toxicity-dependent feasibility bound approach provides improved MTD recommendation properties to the original EWOC approach for both discrete and continuous doses across most dose-toxicity scenarios, with comparable performance to other approaches without recommending incoherent dose escalation. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.
Date Issued
2017-07-20
Date Acceptance
2017-02-18
Citation
Statistics in Medicine, 2017, 36 (16), pp.2499-2513
ISSN
0277-6715
Publisher
John Wiley and Sons
Start Page
2499
End Page
2513
Journal / Book Title
Statistics in Medicine
Volume
36
Issue
16
Copyright Statement
© 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd
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://www.ncbi.nlm.nih.gov/pubmed/28295513
Subjects
Bayesian adaptive designs
dose-escalation
maximum tolerated dose
phase I trials
Antineoplastic Agents
Bayes Theorem
Biostatistics
Clinical Trials, Phase I as Topic
Computer Simulation
Drug Overdose
Feasibility Studies
Humans
Maximum Tolerated Dose
Neoplasms
Publication Status
Published
Coverage Spatial
England
Date Publish Online
2017-03-15