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

TitleAssessing the dependence of sensitivity and specificity on prevalence in meta-analysis.
Publication TypeJournal Article
Year of Publication2011
AuthorsLi, Jialiang, and Jason P. Fine
JournalBiostatistics
Volume12
Issue4
Pagination710-22
Date Published2011 Oct
ISSN1468-4357
KeywordsBiomarkers, Tumor, Biostatistics, CA-125 Antigen, Diagnostic Imaging, Female, Humans, Meta-Analysis as Topic, Models, Statistical, Neoplasms, Ovarian Neoplasms, Positron-Emission Tomography, Prevalence, Sensitivity and Specificity, Tomography, X-Ray Computed
Abstract

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.

DOI10.1093/biostatistics/kxr008
Alternate JournalBiostatistics
Original PublicationAssessing the dependence of sensitivity and specificity on prevalence in meta-analysis.
PubMed ID21525421
PubMed Central IDPMC4042906
Grant ListP01 CA142538 / CA / NCI NIH HHS / United States
P30 AI050410 / AI / NIAID NIH HHS / United States
R01 CA094893 / CA / NCI NIH HHS / United States
Project: