IDEAS home Printed from https://ideas.repec.org/a/taf/jnlasa/v108y2013i503p892-901.html
   My bibliography  Save this article

A Phase I Bayesian Adaptive Design to Simultaneously Optimize Dose and Schedule Assignments Both Between and Within Patients

Author

Listed:
  • Jin Zhang
  • Thomas M. Braun

Abstract

In traditional schedule or dose--schedule finding designs, patients are assumed to receive their assigned dose--schedule combination throughout the trial even though the combination may be found to have an undesirable toxicity profile, which contradicts actual clinical practice. Since no systematic approach exists to optimize intrapatient dose--schedule assignment, we propose a Phase I clinical trial design that extends existing approaches to optimize dose and schedule solely between patients by incorporating adaptive variations to dose--schedule assignments within patients as the study proceeds. Our design is based on a Bayesian nonmixture cure rate model that incorporates multiple administrations each patient receives with the per-administration dose included as a covariate. Simulations demonstrate that our design identifies safe dose and schedule combinations as well as the traditional method that does not allow for intrapatient dose--schedule reassignments, but with a larger number of patients assigned to safe combinations. Supplementary materials for this article are available online.

Suggested Citation

  • Jin Zhang & Thomas M. Braun, 2013. "A Phase I Bayesian Adaptive Design to Simultaneously Optimize Dose and Schedule Assignments Both Between and Within Patients," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(503), pages 892-901, September.
  • Handle: RePEc:taf:jnlasa:v:108:y:2013:i:503:p:892-901
    DOI: 10.1080/01621459.2013.806927
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/01621459.2013.806927
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/01621459.2013.806927?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. Yin, Guosheng & Yuan, Ying, 2009. "Bayesian Model Averaging Continual Reassessment Method in Phase I Clinical Trials," Journal of the American Statistical Association, American Statistical Association, vol. 104(487), pages 954-968.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Emma Gerard & Sarah Zohar & Hoai‐Thu Thai & Christelle Lorenzato & Marie‐Karelle Riviere & Moreno Ursino, 2022. "Bayesian dose regimen assessment in early phase oncology incorporating pharmacokinetics and pharmacodynamics," Biometrics, The International Biometric Society, vol. 78(1), pages 300-312, March.
    2. Beibei Guo & Elizabeth Garrett‐Mayer & Suyu Liu, 2021. "A Bayesian phase I/II design for cancer clinical trials combining an immunotherapeutic agent with a chemotherapeutic agent," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(5), pages 1210-1229, November.

    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. 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.
    2. Yimei Li & Ying Yuan, 2020. "PA‐CRM: A continuous reassessment method for pediatric phase I oncology trials with concurrent adult trials," Biometrics, The International Biometric Society, vol. 76(4), pages 1364-1373, December.
    3. Nolan A. Wages & Craig L. Slingluff, 2020. "Flexible Phase I–II Design for Partially Ordered Regimens with Application to Therapeutic Cancer Vaccines," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 12(2), pages 104-123, July.
    4. Jiajing Xu & Guosheng Yin & David Ohlssen & Frank Bretz, 2016. "Bayesian two-stage dose finding for cytostatic agents via model adaptation," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 65(3), pages 465-482, April.
    5. Haitao Pan & Cailin Zhu & Feng Zhang & Ying Yuan & Shemin Zhang & Wenhong Zhang & Chanjuan Li & Ling Wang & Jielai Xia, 2014. "The Continual Reassessment Method for Multiple Toxicity Grades: A Bayesian Model Selection Approach," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-8, May.
    6. Steven B Kim & Dong Sub Kim & Christina Magana-Ramirez, 2021. "Applications of statistical experimental designs to improve statistical inference in weed management," PLOS ONE, Public Library of Science, vol. 16(9), pages 1-21, September.

    More about this item

    Statistics

    Access and download statistics

    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:taf:jnlasa:v:108:y:2013:i:503:p:892-901. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/UASA20 .

    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.