A solution for the most basic optimization problem associated with an ROC curve

In a few cases, such as early pregnancy tests, the test results are dichotomous; many diagnostic tests, however, give results which are not binary. In the diagnosis of prostate cancer, prostate-specific antigen test result is on a continuous scale; or, in radiology, assessment of mammograms is on an ordinal scale. in such cases, the accuracy of the marker or test is often first summarized in a receiver operating characteristic (ROC) curve and then as the area under that curve. The area under the ROC curve, however, only shows the 'potential' of a marker; sooner or later, for practical uses, we still need to dichotomize the test result so that we can classify subjects as 'diseased' or 'healthy'. Finding an 'optimal' cutpoint to dichotomize a continuous marker is desirable and is a very basic problem but, in all or most cases, cutpoints used in practice are arbitrary. The difficulty lies in our failure to define and justify a criterion for optimality. In this paper, we will propose a solution by maximizing a well-known parameter-the Youden's Index-within the framework of the ROC curve.