Abstract
The results of many clinical tests are quantitative and are provided on a continuous scale. To help decide the presence or absence of disease, a cut‐off point for ‘normal’ or ‘abnormal’ is chosen. The sensitivity and specificity of a test vary according to the level that is chosen as the cut‐off point. The receiver operating characteristic (ROC) curve, a graphical technique for describing and comparing the accuracy of diagnostic tests, is obtained by plotting the sensitivity of a test on the y axis against 1‐specificity on the x axis. Two methods commonly used to establish the optimal cut‐off point include the point on the ROC curve closest to (0, 1) and the Youden index. The area under the ROC curve provides a measure of the overall performance of a diagnostic test. In this paper, the author explains how the ROC curve can be used to select optimal cut‐off points for a test result, to assess the diagnostic accuracy of a test, and to compare the usefulness of tests.Conclusion: The ROC curve is obtained by calculating the sensitivity and specificity of a test at every possible cut‐off point, and plotting sensitivity against 1‐specificity. The curve may be used to select optimal cut‐off values for a test result, to assess the diagnostic accuracy of a test, and to compare the usefulness of different tests.