Comparing and optimizing diagnostic tests: an information-theoretical approach.

Abstract

An ideal method for assessing performance of non-binary diagnostic tests would specify each test's optimal operating point and would tell a diagnostician which of many tests was the best one to use in a particular clinical situation. This article shows how information theory and receiver operating characteristic (ROC) analysis can be combined to evaluate and compare diagnostic tests at their optimum cutoffs once disease prevalence and test properties are specified. Though it is not appropriate for all clinical situations, the method can be used for most diagnostic tests whenever information is desired for its own sake or when reducing uncertainty is the goal of testing. The method also is appropriate in those situations where benefits and costs cannot be specified precisely enough to permit test optimization based on a balancing of anticipated goods and evils.