A Solution for the Most Basic Optimization Problem Associated with an ROC Curve

Chap Le
Division of Biostatistics and Cancer Center
University of Minnesota

Wednesday, September 27th 2006
3:30pm
Moos 2-690
Minneapolis Campus

Abstract:
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, PSA (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 "non-diseased". Finding an "optimal" cut-point to dichotomize a continuous marker is desirable and is a very basic problem but, in all or most cases, cut-points used in practice are arbitrary. The difficulty lies in our failure to define and justify a criterion for optimality. In this talk - and a paper appearing soon on Statistical Methods in Medical research, we will propose a solution by maximizing a well-known parameter - the Youden's Index - within the framework of the ROC curve. This is aimed as an illustration of Translation Research.

A social tea will be held at 3:00 P.M. in A434 Mayo. All are Welcome.
For more details contact 612-624-4655 or see http://www.biostat.umn.edu/seminar_academic.html