Assessing the dependence of sensitivity and specificity on prevalence in meta-analysis

Biostatistics. 2011 Oct;12(4):710-22. doi: 10.1093/biostatistics/kxr008. Epub 2011 Apr 27.


We consider modeling the dependence of sensitivity and specificity on the disease prevalence in diagnostic accuracy studies. Many meta-analyses compare test accuracy across studies and fail to incorporate the possible connection between the accuracy measures and the prevalence. We propose a Pearson type correlation coefficient and an estimating equation-based regression framework to help understand such a practical dependence. The results we derive may then be used to better interpret the results from meta-analyses. In the biomedical examples analyzed in this paper, the diagnostic accuracy of biomarkers are shown to be associated with prevalence, providing insights into the utility of these biomarkers in low- and high-prevalence populations.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomarkers, Tumor / analysis
  • Biostatistics
  • CA-125 Antigen / analysis
  • Diagnostic Imaging
  • Female
  • Humans
  • Meta-Analysis as Topic*
  • Models, Statistical
  • Neoplasms / diagnosis
  • Ovarian Neoplasms / diagnosis
  • Positron-Emission Tomography
  • Prevalence*
  • Sensitivity and Specificity
  • Tomography, X-Ray Computed


  • Biomarkers, Tumor
  • CA-125 Antigen