Meta-analysis of diagnostic test accuracy assessment studies with varying number of thresholds

Biometrics. 2003 Dec;59(4):936-46. doi: 10.1111/j.0006-341x.2003.00108.x.


Current meta-analytic methods for diagnostic test accuracy are generally applicable to a selection of studies reporting only estimates of sensitivity and specificity, or at most, to studies whose results are reported using an equal number of ordered categories. In this article, we propose a new meta-analytic method to evaluate test accuracy and arrive at a summary receiver operating characteristic (ROC) curve for a collection of studies evaluating diagnostic tests, even when test results are reported in an unequal number of nonnested ordered categories. We discuss both non-Bayesian and Bayesian formulations of the approach. In the Bayesian setting, we propose several ways to construct summary ROC curves and their credible bands. We illustrate our approach with data from a recently published meta-analysis evaluating a single serum progesterone test for diagnosing pregnancy failure.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Bayes Theorem
  • Biometry / methods*
  • False Positive Reactions
  • Female
  • Humans
  • Meta-Analysis as Topic
  • Models, Statistical*
  • Pregnancy
  • Pregnancy Outcome
  • Pregnancy, Ectopic
  • ROC Curve
  • Reproducibility of Results
  • Sensitivity and Specificity