IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-642-55345-5_15.html
   My bibliography  Save this book chapter

Dose-Finding Methods for Two-Agent Combination Phase I Trials

In: Developments in Statistical Evaluation of Clinical Trials

Author

Listed:
  • Akihiro Hirakawa

    (Nagoya University Graduate School of Medicine, Center for Advanced Medicine and Clinical Research)

  • Shigeyuki Matsui

    (Nagoya University Graduate School of Medicine, Department of Biostatistics)

Abstract

In this chapter, we discuss the toxicity-based dose-finding methods for two-agent combinations in phase I oncology trials. The model-based approaches, such as the continual reassessment method (CRM), have been gradually applied to single-agent trials to determine the maximum tolerated dose (MTD). By contrast, the rule-based approaches have commonly been applied to two-agent combination trials, probably due to the absence of well-understood model-based methods for two-agent combination trials. In developing a dose-finding method for two-agent combination trials, we require a reasonable model that can adequately capture joint toxicity probabilities for two agents, taking into consideration of possible interactions of the two agents on toxicity probability (such as synergistic or antagonistic effects). We provide an overview of two useful dose-finding approaches based on Bayesian copula-type models and partial orderings across dose levels for two-agent combination trials. We also supply examples of successful software implementations and discuss the operating characteristics of these approaches.

Suggested Citation

  • Akihiro Hirakawa & Shigeyuki Matsui, 2014. "Dose-Finding Methods for Two-Agent Combination Phase I Trials," Springer Books, in: Kees van Montfort & Johan Oud & Wendimagegn Ghidey (ed.), Developments in Statistical Evaluation of Clinical Trials, edition 127, chapter 0, pages 265-282, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-55345-5_15
    DOI: 10.1007/978-3-642-55345-5_15
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:spr:sprchp:978-3-642-55345-5_15. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.