IDEAS home Printed from https://ideas.repec.org/p/boc/lsug23/15.html
   My bibliography  Save this paper

Facilities for optimising and designing multi-arm multi-stage (MAMS) randomised controlled trials with binary outcomes

Author

Listed:
  • Babak Choodari-Oskooei

    (MRC Clinical Trials Unit at UCL, University College London)

  • Daniel J. Bratton
  • Mahesh KB Parmar

Abstract

In this talk, we introduce two Stata programs nstagebin and nstagebinopt which can be used to facilitate the design of multi-arm multi-stage (MAMS) trials with binary outcomes. MAMS designs are a class of efficient and adaptive randomised clinical trials that have successfully been used in many disease areas, including cancer, TB, maternal health, COVID-19, and surgery. The nstagebinopt program finds a class of efficient “admissible” designs based on an optimality criterion using a systematic search procedure. The nstagebin command calculates the stagewise sample sizes, trial timelines, and the overall operating characteristics of MAMS design with binary outcomes. Both programs allow the use of Dunnett's correction to account for multiple testing. We also use the ROSSINI 2 MAMS design, an ongoing MAMS trial in surgical wound infection, to illustrate the capabilities of both programs. The new Stata programs facilitate the design of MAMS trials with binary outcomes where more than one research question can be addressed under one protocol.

Suggested Citation

  • Babak Choodari-Oskooei & Daniel J. Bratton & Mahesh KB Parmar, 2023. "Facilities for optimising and designing multi-arm multi-stage (MAMS) randomised controlled trials with binary outcomes," UK Stata Conference 2023 15, Stata Users Group.
  • Handle: RePEc:boc:lsug23:15
    as

    Download full text from publisher

    File URL: http://repec.org/lsug2023/Stata_UK23_Chooderi-Oskooei.pptx
    Download Restriction: no
    ---><---

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:boc:lsug23:15. 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: Christopher F Baum (email available below). General contact details of provider: https://edirc.repec.org/data/stataea.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.