IDEAS home Printed from https://ideas.repec.org/a/spr/stpapr/v59y2018i2d10.1007_s00362-016-0790-7.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00362-016-0790-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s00362-016-0790-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Anastasia Ivanova & Se Hee Kim, 2009. "Dose Finding for Continuous and Ordinal Outcomes with a Monotone Objective Function: A Unified Approach," Biometrics, The International Biometric Society, vol. 65(1), pages 307-315, March.
    2. 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.
    3. Erica Brittain & Dean Follmann & Song Yang, 2008. "Dynamic Comparison of Kaplan–Meier Proportions: Monitoring a Randomized Clinical Trial with a Long-Term Binary Endpoint," Biometrics, The International Biometric Society, vol. 64(1), pages 189-197, March.
    4. Yifei Zhang & Sha Cao & Chi Zhang & Ick Hoon Jin & Yong Zang, 2021. "A Bayesian adaptive phase I/II clinical trial design with late‐onset competing risk outcomes," Biometrics, The International Biometric Society, vol. 77(3), pages 796-808, September.
    5. Thomas M. Braun, 2018. "Motivating sample sizes in adaptive Phase I trials via Bayesian posterior credible intervals," Biometrics, The International Biometric Society, vol. 74(3), pages 1065-1071, September.
    6. Changying A. Liu & Thomas M. Braun, 2009. "Parametric non‐mixture cure models for schedule finding of therapeutic agents," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 58(2), pages 225-236, May.
    7. B. Nebiyou Bekele & Yisheng Li & Yuan Ji, 2010. "Risk-Group-Specific Dose Finding Based on an Average Toxicity Score," Biometrics, The International Biometric Society, vol. 66(2), pages 541-548, June.
    8. Nadine Houede & Peter F. Thall & Hoang Nguyen & Xavier Paoletti & Andrew Kramar, 2010. "Utility-Based Optimization of Combination Therapy Using Ordinal Toxicity and Efficacy in Phase I/II Trials," Biometrics, The International Biometric Society, vol. 66(2), pages 532-540, June.
    9. Alessandra Giovagnoli, 2021. "The Bayesian Design of Adaptive Clinical Trials," IJERPH, MDPI, vol. 18(2), pages 1-15, January.
    10. Ying Kuen Cheung, 2002. "On the Use of Nonparametric Curves in Phase I Trials with Low Toxicity Tolerance," Biometrics, The International Biometric Society, vol. 58(1), pages 237-240, March.
    11. Yuan Ji & B. Nebiyou Bekele, 2009. "Adaptive Randomization for Multiarm Comparative Clinical Trials Based on Joint Efficacy/Toxicity Outcomes," Biometrics, The International Biometric Society, vol. 65(3), pages 876-884, September.
    12. Tianjian Zhou & Wentian Guo & Yuan Ji, 2020. "PoD-TPI: Probability-of-Decision Toxicity Probability Interval Design to Accelerate Phase I Trials," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 12(2), pages 124-145, July.
    13. Ying Kuen Cheung & Rick Chappell, 2002. "A Simple Technique to Evaluate Model Sensitivity in the Continual Reassessment Method," Biometrics, The International Biometric Society, vol. 58(3), pages 671-674, September.
    14. Peter F. Thall & Hoang Q. Nguyen & Thomas M. Braun & Muzaffar H. Qazilbash, 2013. "Using Joint Utilities of the Times to Response and Toxicity to Adaptively Optimize Schedule–Dose Regimes," Biometrics, The International Biometric Society, vol. 69(3), pages 673-682, September.
    15. Nigel Stallard & Peter F. Thall, 2001. "Decision-Theoretic Designs for Pre-Phase II Screening Trials in Oncology," Biometrics, The International Biometric Society, vol. 57(4), pages 1089-1095, December.
    16. Alexander M. Kaizer & Brian P. Hobbs & Joseph S. Koopmeiners, 2018. "A multi‐source adaptive platform design for testing sequential combinatorial therapeutic strategies," Biometrics, The International Biometric Society, vol. 74(3), pages 1082-1094, September.
    17. Azriel, David, 2014. "Optimal sequential designs in phase I studies," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 288-297.
    18. Oron Assaf P. & Azriel David & Hoff Peter D., 2011. "Dose-Finding Designs: The Role of Convergence Properties," The International Journal of Biostatistics, De Gruyter, vol. 7(1), pages 1-17, October.
    19. Ying Kuen Cheung & Peter F. Thall, 2002. "Monitoring the Rates of Composite Events with Censored Data in Phase II Clinical Trials," Biometrics, The International Biometric Society, vol. 58(1), pages 89-97, March.
    20. Ying Kuen Cheung, 2014. "Simple benchmark for complex dose finding studies," Biometrics, The International Biometric Society, vol. 70(2), pages 389-397, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:stpapr:v:59:y:2018:i:2:d:10.1007_s00362-016-0790-7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.