Donate Help Contact The AHA Sign In Home
American Heart Association
Circulation
Search: search_blue_button Advanced Search
Circulation. 2007;115:654-657
doi: 10.1161/CIRCULATIONAHA.105.594929
This Article
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow Request Permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Zou, K. H.
Right arrow Articles by Mauri, L.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Zou, K. H.
Right arrow Articles by Mauri, L.
Related Collections
Right arrow Health policy and outcome research
Right arrow Other diagnostic testing
Right arrow Epidemiology

(Circulation. 2007;115:654-657.)
© 2007 American Heart Association, Inc.


Statistical Primer for Cardiovascular Research

Receiver-Operating Characteristic Analysis for Evaluating Diagnostic Tests and Predictive Models

Kelly H. Zou, PhD; A. James O’Malley, PhD; Laura Mauri, MD, MSc

From Children’s Hospital Boston (K.H.Z.), Harvard Medical School (K.H.Z., A.J.O., L.M.), Brigham and Women’s Hospital (L.M.), and Harvard Clinical Research Institute (L.M.), Boston, Mass.

Correspondence to Kelly H. Zou, PhD, Department of Health Care Policy, Harvard Medical School, 180 Longwood Ave, Boston, MA 02115. E-mail kelly.zou@childrens.harvard.edu


Key Words: diagnosis • ROC curve • sensitivity and specificity • statistics • tests


An extract of the first 250 words of the full text is provided, because this article has no abstract.
 


*    Introduction
 
Receiver-operating characteristic (ROC) analysis was originally developed during World War II to analyze classification accuracy in differentiating signal from noise in radar detection.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.10

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. 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. 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). Predictive modeling to estimate expected outcomes such as mortality or adverse cardiac events based on patient risk characteristics also is common in cardiovascular research. ROC analysis is a useful tool in both of these situations.

In this article, we begin by reviewing the measures of accuracy—sensitivity, specificity, and area under the curve (AUC)—that use the ROC curve. We also illustrate how these measures can be applied using the evaluation of a hypothetical new diagnostic test as an example.


*    Diagnostic Test and Predictive Model
 
A diagnostic classification test typically yields binary, ordinal, or continuous outcomes. The simplest type, binary . . . [Full Text of this Article]




This article has been cited by other articles:


Home page
Eur Heart JHome page
R. C. Saumarez, M. Pytkowski, M. Sterlinski, J. P. Bourke, J. R. Clague, S. M. Cobbe, D. T. Connelly, M. J. Griffith, P. P. McKeown, K. McLeod, et al.
Paced ventricular electrogram fractionation predicts sudden cardiac death in hypertrophic cardiomyopathy
Eur. Heart J., July 1, 2008; 29(13): 1653 - 1661.
[Abstract] [Full Text] [PDF]


Home page
J. Am. Soc. Nephrol.Home page
K. Rossing, H. Mischak, M. Dakna, P. Zurbig, J. Novak, B. A. Julian, D. M. Good, J. J. Coon, L. Tarnow, P. Rossing, et al.
Urinary Proteomics in Diabetes and CKD
J. Am. Soc. Nephrol., July 1, 2008; 19(7): 1283 - 1290.
[Abstract] [Full Text] [PDF]


Home page
Br J AnaesthHome page
A. Levrat, A. Gros, L. Rugeri, K. Inaba, B. Floccard, C. Negrier, and J.-S. David
Evaluation of rotation thrombelastography for the diagnosis of hyperfibrinolysis in trauma patients
Br. J. Anaesth., June 1, 2008; 100(6): 792 - 797.
[Abstract] [Full Text] [PDF]


Home page
CirculationHome page
R. Hachamovitch and M. F. Di Carli
Methods and Limitations of Assessing New Noninvasive Tests: Part I: Anatomy-Based Validation of Noninvasive Testing
Circulation, May 20, 2008; 117(20): 2684 - 2690.
[Full Text] [PDF]


Home page
Eur Heart JHome page
J. Schwitter, C. M. Wacker, A. C. van Rossum, M. Lombardi, N. Al-Saadi, H. Ahlstrom, T. Dill, H. B.W. Larsson, S. D. Flamm, M. Marquardt, et al.
MR-IMPACT: comparison of perfusion-cardiac magnetic resonance with single-photon emission computed tomography for the detection of coronary artery disease in a multicentre, multivendor, randomized trial
Eur. Heart J., February 2, 2008; 29(4): 480 - 489.
[Abstract] [Full Text] [PDF]


Home page
J. Appl. Physiol.Home page
C. L. del Rio, P. I. McConnell, M. Kukielka, R. Dzwonczyk, B. D. Clymer, M. B. Howie, and G. E. Billman
Electrotonic remodeling following myocardial infarction in dogs susceptible and resistant to sudden cardiac death
J Appl Physiol, February 1, 2008; 104(2): 386 - 393.
[Abstract] [Full Text] [PDF]


Home page
Am. J. Roentgenol.Home page
A. R. Hunsaker, K. H. Zou, A. C. Poh, B. Trotman-Dickenson, F. L. Jacobson, R. R. Gill, and S. Z. Goldhaber
Routine Pelvic and Lower Extremity CT Venography in Patients Undergoing Pulmonary CT Angiography
Am. J. Roentgenol., February 1, 2008; 190(2): 322 - 326.
[Abstract] [Full Text] [PDF]


Home page
Clin. Chem.Home page
N. R. Cook
Statistical Evaluation of Prognostic versus Diagnostic Models: Beyond the ROC Curve
Clin. Chem., January 1, 2008; 54(1): 17 - 23.
[Abstract] [Full Text] [PDF]