Predictive modeling to estimate expected outcomes such as mortality or adverse cardiac events based on patient risk characteristics also is common in cardiovascular research. In Circulation from January 1, 1995, through December 5, 2005, 309 articles were published with the key phrase “receiver operating characteristic.” In cardiology, diagnostic testing plays a fundamental role in clinical practice (eg, serum markers of myocardial necrosis, cardiac imaging tests). Its function as a simple graphical tool for displaying the accuracy of a medical diagnostic test is one of the most well-known applications of ROC curve analysis. ROC analysis is a useful tool for evaluating the performance of diagnostic tests and more generally for evaluating the accuracy of a statistical model (eg, logistic regression, linear discriminant analysis) that classifies subjects into 1 of 2 categories, diseased or nondiseased.
1 Recently, the methodology has been adapted to several clinical areas heavily dependent on screening and diagnostic tests, 2–4 in particular, laboratory testing, 5 epidemiology, 6 radiology, 7–9 and bioinformatics. Receiver-operating characteristic (ROC) analysis was originally developed during World War II to analyze classification accuracy in differentiating signal from noise in radar detection. Customer Service and Ordering Information.Stroke: Vascular and Interventional Neurology.Journal of the American Heart Association (JAHA).Circ: Cardiovascular Quality & Outcomes.
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