Sensitivity, Specificity, Receiver-Operating Characteristic (ROC) Curves and Likelihood Ratios: Communicating the Performance of Diagnostic Tests
Christopher M Florkowski



Summary
• Diagnostic accuracy studies address how well a test identifies the target condition of interest.
• Sensitivity, specificity, predictive values and likelihood ratios (LRs) are all different ways of expressing test performance.
• Receiver operating characteristic (ROC) curves compare sensitivity versus specificity across a range of values for the ability to predict a dichotomous outcome. Area under the ROC curve is another measure of test performance.
• All of these parameters are not intrinsic to the test and are determined by the clinical context in which the test is employed.
• High sensitivity corresponds to high negative predictive value and is the ideal property of a “rule-out” test.
• High specificity corresponds to high positive predictive value and is the ideal property of a “rule-in” test.
• LRs leverage pre-test into post-test probabilities of a condition of interest and there is some evidence that they are more intelligible to users.

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