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Toxicity-dependent feasibility bounds for the Escalation with Overdose Control approach in phase I cancer trials

Wheeler, GM; Sweeting, MJ; Mander, AP; (2017) Toxicity-dependent feasibility bounds for the Escalation with Overdose Control approach in phase I cancer trials. Statistics in Medicine , 36 (16) pp. 2499-2513. 10.1002/sim.7280. Green open access

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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.

Type: Article
Title: Toxicity-dependent feasibility bounds for the Escalation with Overdose Control approach in phase I cancer trials
Open access status: An open access version is available from UCL Discovery
DOI: 10.1002/sim.7280
Publisher version: http://dx.doi.org/10.1002/sim.7280
Language: English
Additional information: Copyright © 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 (http://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Cancer Institute
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Cancer Institute > CRUK Cancer Trials Centre
URI: https://discovery.ucl.ac.uk/id/eprint/1542977
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