title: Receiver operating characteristic curve analysis of clinical risk models.
abstract: 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.
authors.affiliation: Providence Health System, Portland, Oregon, USA. ggrunkemeier@providence.org
authors.forename: G L
authors.initials: GL
authors.lastname: Grunkemeier
authors.forename: R
authors.initials: R
authors.lastname: Jin
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001026:Coronary Artery Bypass / Q000401:mortality*; D005260:Female; D006305:Health Status Indicators; D017052:Hospital Mortality; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D011336:Probability; D012372:ROC Curve; D012680:Sensitivity and Specificity; D014481:United States