Sensitivity, specificity, receiver-operating characteristic (ROC) curves and likelihood ratios: communicating the performance of diagnostic tests.

* 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.