IDEAS home Printed from
   My bibliography  Save this article

The Myth of Making Inferences for an Overall Treatment Efficacy with Data from Multiple Comparative Studies Via Meta-Analysis


  • Takahiro Hasegawa

    (Shionogi & Co., Ltd.)

  • Brian Claggett

    () (Brigham and Women’s Hospital)

  • Lu Tian

    (Stanford University School of Medicine)

  • Scott D. Solomon

    (Brigham and Women’s Hospital)

  • Marc A. Pfeffer

    (Brigham and Women’s Hospital)

  • Lee-Jen Wei

    () (Harvard University)


Abstract Meta-analysis techniques, if applied appropriately, can provide a summary of the totality of evidence regarding an overall difference between a new treatment and a control group using data from multiple comparative clinical studies. The standard meta-analysis procedures, however, may not give a meaningful between-group difference summary measure or identify a meaningful patient population of interest, especially when the fixed-effect model assumption is not met. Moreover, a single between-group comparison measure without a reference value obtained from patients in the control arm would likely not be informative enough for clinical decision making. In this paper, we propose a simple, robust procedure based on a mixture population concept and provide a clinically meaningful group contrast summary for a well-defined target population. We use the data from a recent meta-analysis for evaluating statin therapies with respect to the incidence of fatal stroke events to illustrate the issues associated with the standard meta-analysis procedures as well as the advantages of our simple proposal.

Suggested Citation

  • Takahiro Hasegawa & Brian Claggett & Lu Tian & Scott D. Solomon & Marc A. Pfeffer & Lee-Jen Wei, 0. "The Myth of Making Inferences for an Overall Treatment Efficacy with Data from Multiple Comparative Studies Via Meta-Analysis," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 0, pages 1-14.
  • Handle: RePEc:spr:stabio:v::y::i::d:10.1007_s12561-016-9179-3
    DOI: 10.1007/s12561-016-9179-3

    Download full text from publisher

    File URL:
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

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

    References listed on IDEAS

    1. Julian P. T. Higgins & Simon G. Thompson & David J. Spiegelhalter, 2009. "A re-evaluation of random-effects meta-analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(1), pages 137-159.
    Full references (including those not matched with items on IDEAS)


    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:stabio:v::y::i::d:10.1007_s12561-016-9179-3. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla) or (Andrew Huffard) The email address of this maintainer does not seem to be valid anymore. Please ask Andrew Huffard to update the entry or send us the correct email address. General contact details of provider: .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.