Estimating the Relative Utility of Screening Mammography.

Source

Department of Psychology, University of California, Santa Barbara, CA (CKA, ME).

Abstract

BACKGROUND:

The concept of diagnostic utility is a fundamental component of signal detection theory, going back to some of its earliest works. Attaching utility values to the various possible outcomes of a diagnostic test should, in principle, lead to meaningful approaches to evaluating and comparing such systems. However, in many areas of medical imaging, utility is not used because it is presumed to be unknown.

METHODS:

In this work, we estimate relative utility (the utility benefit of a detection relative to that of a correct rejection) for screening mammographyusing its known relation to the slope of a receiver operating characteristic (ROC) curve at the optimal operating point. The approach assumes that the clinical operating point is optimal for the goal of maximizing expected utility and therefore the slope at this point implies a value of relative utility for the diagnostic task, for known disease prevalence. We examine utility estimation in the context of screening mammography using the Digital Mammographic Imaging Screening Trials (DMIST) data.

RESULTS:

We show how various conditions can influence the estimated relative utility, including characteristics of the rating scale, verification time, probability model, and scope of the ROC curve fit. Relative utility estimates range from 66 to 227.

CONCLUSIONS:

We argue for one particular set of conditions that results in a relative utility estimate of 162 (±14%). This is broadly consistent with values in screening mammography determined previously by other means. At the disease prevalence found in the DMIST study (0.59% at 365-day verification), optimal ROC slopes are near unity, suggesting that utility-based assessments of screening mammography will be similar to those found using Youden's index.

TimAllenMDJD

Sunday, April 14, 2013