IDEAS home Printed from https://ideas.repec.org/a/bla/jorssc/v68y2019i2p271-288.html
   My bibliography  Save this article

Semiparametric dose finding methods: special cases

Author

Listed:
  • M. Clertant
  • J. O’Quigley

Abstract

A broad structure for the design and analysis of early phase clinical trials has recently been presented. The approach is described as being semiparametric in that the dose–toxicity function is modelled through a parameter of interest and a nuisance parameter. Although very general, the semiparametric method SPM allows for the possibility of specific calibration. In particular, it is shown that we can obtain identical operating characteristics of more richly parameterized designs such as the continual reassessment method. Here, we consider several other designs that have weaker parameterizations than the continual reassessment method, in particular the cumulative cohort distributions design, the modified toxicity probability interval design, the Bayesian optimal interval design and the keyboard design. We show that all of these designs are included, as special cases, in the semiparametric framework. It becomes immediately apparent how to structure any investigation into the operating characteristics of these designs as well as how to tune any design further with the purpose of improving on these characteristics. Simulations are provided to give added support to these findings.

Suggested Citation

  • M. Clertant & J. O’Quigley, 2019. "Semiparametric dose finding methods: special cases," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 68(2), pages 271-288, February.
  • Handle: RePEc:bla:jorssc:v:68:y:2019:i:2:p:271-288
    DOI: 10.1111/rssc.12308
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/rssc.12308
    Download Restriction: no

    File URL: https://libkey.io/10.1111/rssc.12308?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
    ---><---

    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:bla:jorssc:v:68:y:2019:i:2:p:271-288. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.html .

    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.