abstract
- Clinical decision-making relies heavily on making a correct diagnosis. Clinicians have a responsibility to understand the full spectrum of the diagnostic information conveyed by a physical exam finding, laboratory test result, or imaging. Many laboratory tests, such as troponin and B-type natriuretic peptide (BNP), are continuous tests with many possible results. Yet, there is a tendency to dichotomize tests into positive and negative, and use sensitivity and specificity to describe the test characteristics. This approach can lead to waste of important diagnostic information and substandard clinical decision-making. The aim of this paper is to demonstrate the role of ROC curves in developing a more comprehensive understanding of diagnostic information portrayed by continuous tests to augment clinical decision-making.