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Incoherent dose-escalation in phase I trials using the escalation with overdose control approach

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  • Graham M. Wheeler

    (Cambridge Institute of Public Health
    University College London)

Abstract

A desirable property of any dose-escalation strategy for phase I oncology trials is coherence: if the previous patient experienced a toxicity, a higher dose is not recommended for the next patient; similarly, if the previous patient did not experience a toxicity, a lower dose is not recommended for the next patient. The escalation with overdose control (EWOC) approach is a model-based design that has been applied in practice, under which the dose assigned to the next patient is the one that, given all available data, has a posterior probability of exceeding the maximum tolerated dose equal to a pre-specified value known as the feasibility bound. Several methodological and applied publications have considered the EWOC approach with both feasibility bounds fixed and increasing throughout the trial. Whilst the EWOC approach with fixed feasibility bound has been proven to be coherent, some proposed methods of increasing the feasibility bound regardless of toxicity outcomes of patients can lead to incoherent dose-escalation. This paper formalises a proof that incoherent dose-escalation can occur if the feasibility bound is increased without consideration of preceding toxicity outcomes, and shows via simulation studies that only small increases in the feasibility bound are required for incoherent dose-escalations to occur.

Suggested Citation

  • Graham M. Wheeler, 2018. "Incoherent dose-escalation in phase I trials using the escalation with overdose control approach," Statistical Papers, Springer, vol. 59(2), pages 801-811, June.
    • Handle: RePEc:spr:stpapr:v:59:y:2018:i:2:d:10.1007_s00362-016-0790-7
    DOI: 10.1007/s00362-016-0790-7
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    References listed on IDEAS

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    1. Zacks, S. & Rogatko, A. & Babb, J., 1998. "Optimal Bayesian-feasible dose escalation for cancer phase I trials," Statistics & Probability Letters, Elsevier, vol. 38(3), pages 215-220, June.
    2. Ying Kuen Cheung & Rick Chappell, 2000. "Sequential Designs for Phase I Clinical Trials with Late-Onset Toxicities," Biometrics, The International Biometric Society, vol. 56(4), pages 1177-1182, December.
    3. Jay Bartroff & Tze Leung Lai, 2011. "Incorporating Individual and Collective Ethics into Phase I Cancer Trial Designs," Biometrics, The International Biometric Society, vol. 67(2), pages 596-603, June.
    4. Ying Kuen Cheung, 2005. "Coherence principles in dose-finding studies," Biometrika, Biometrika Trust, vol. 92(4), pages 863-873, December.
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