IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-981-10-0126-0_16.html

Meta-Analysis of Prognostic Studies Evaluating Time-Dependent Diagnostic and Predictive Capacities of Biomarkers

In: Frontiers of Biostatistical Methods and Applications in Clinical Oncology

Author

Listed:
  • Satoshi Hattori

    (Osaka University, Department of Integrated Medicine, Biomedical Statistics)

  • Xiao-Hua Zhou

    (VA Puget Sound Health Care System, HSR&D Center of Excellence
    University of Washington, Department of Biostatistics)

Abstract

Prognostic biomarker studies, which examine the associationAssociation between biomarkers and patients’ prognoses, have played important roles in clinical decision making. Since prognostic studies are often conducted with small sample sizes in a limited number of centers, meta-analysis is expected to be a powerful tool to obtain sound evidence on prognostic biomarkers. However, the application of meta-analysis of prognostic studies has been limited partly due to the lack of sound statistical methods. In this chapter, we introduce some recently developed methods useful for the evaluation of diagnostic or predictive capacities of biomarkers for binary or time-to-event outcomes. In addition, we newly present a novel method to estimate the time-dependent positive and negative predictive value curves based on Meta analysis meta-analysis.

Suggested Citation

  • Satoshi Hattori & Xiao-Hua Zhou, 2017. "Meta-Analysis of Prognostic Studies Evaluating Time-Dependent Diagnostic and Predictive Capacities of Biomarkers," Springer Books, in: Shigeyuki Matsui & John Crowley (ed.), Frontiers of Biostatistical Methods and Applications in Clinical Oncology, pages 257-273, Springer.
    • Handle: RePEc:spr:sprchp:978-981-10-0126-0_16
    DOI: 10.1007/978-981-10-0126-0_16
    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:978-981-10-0126-0_16. 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.