Comparison of logistic regression and Bayesian-based algorithms to estimate posttest probability in patients with suspected coronary artery disease undergoing exercise ECG

Receiver operating characteristic curve analysis of clinical risk models

Receiver operating characteristic (ROC) curve analysis is a useful method to measure the ability of a clinical risk model to discriminate between hospital deaths and survivors. Its use in medicine originated as a method for synthesizing the specificity and sensitivity of diagnostic tests across a spectrum of possible cut points. The area under the ROC curve can be interpreted as a probability of correct classification or prediction. We illustrate its use in three steps: first, with a dichotomous variable to introduce specificity and sensitivity; next, with a categorical risk factor (surgical urgency) to produce a primitive ROC curve; and finally, with a continuous risk factor (age) to approximate the usual ROC curve used for clinical risk models.