Chapter 8: Meta-analysis of test performance when there is a "gold standard"

Thomas A. Trikalinos, Cynthia M. Balion, Craig I. Coleman, Lauren Griffith, Pasqualina L. Santaguida, Ben Vandermeer, Rongwei Fu

Research output: Contribution to journalArticlepeer-review

63 Scopus citations


Synthesizing information on test performance metrics such as sensitivity, specificity, predictive values and likelihood ratios is often an important part of a systematic review of a medical test. Because many metrics of test performance are of interest, the meta-analysis of medical tests is more complex than the meta-analysis of interventions or associations. Sometimes, a helpful way to summarize medical test studies is to provide a "summary point", a summary sensitivity and a summary specificity. Other times, when the sensitivity or specificity estimates vary widely or when the test threshold varies, it is more helpful to synthesize data using a "summary line" that describes how the average sensitivity changes with the average specificity. Choosing the most helpful summary is subjective, and in some cases both summaries provide meaningful and complementary information. Because sensitivity and specificity are not independent across studies, the meta-analysis of medical tests is fundamentaly a multivariate problem, and should be addressed with multivariate methods. More complex analyses are needed if studies report results at multiple thresholds for positive tests. At the same time, quantitative analyses are used to explore and explain any observed dissimilarity (heterogeneity) in the results of the examined studies. This can be performed in the context of proper (multivariate) meta-regressions.

Original languageEnglish (US)
Pages (from-to)S56-S66
JournalJournal of general internal medicine
Issue numberSUPPL.1
StatePublished - Jun 2012


  • gold standard
  • meta-analysis
  • test performance

ASJC Scopus subject areas

  • Internal Medicine


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