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Toxicity‐dependent feasibility bounds for the escalation with overdose control approach in phase I cancer trials

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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… Click to show full 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.

Keywords: dependent feasibility; feasibility; approach; escalation; toxicity dependent

Journal Title: Statistics in Medicine
Year Published: 2017

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