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.
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Chap T
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School of Public Health, Division of Biostatistics and Cancer Center, University of Minnesota, MMC 303, Minneapolis 55455, USA. chap@biostat.umn.edu
D014408:Biomarkers, Tumor; D006801:Humans; D008403:Mass Screening; D015233:Models, Statistical; D009369:Neoplasms / Q000175:diagnosis*; D011379:Prognosis; D016016:Proportional Hazards Models; D012372:ROC Curve
D014408:Biomarkers, Tumor