Nancy R. Cook, ScD; Paul M Ridker, MD
Grant Support: By the Donald W. Reynolds Foundation (Dr. Ridker), and the Leducq Foundation (Dr. Ridker). The overall Women's Health Study is supported by grants from the National Heart, Lung, and Blood Institute and the National Cancer Institute (HL-43851 and CA-47988).
Potential Financial Conflicts of Interest:Consultancies: P.M Ridker (AstraZeneca, Schering-Plough, Sanofi Aventis, ISIS, Siemens, Merck, Novartis, Vascular Biogenics). Grants received: P.M Ridker (National Heart, Lung, and Blood Institute, National Cancer Institute, Donald W. Reynolds Foundation, Leducq Foundation, AstraZeneca, Merck, Novartis, Abbott, Roche, Sanofi Aventis). Patents received: P.M Ridker (Brigham and Women's Hospital). Royalties: P.M Ridker (Brigham and Women's Hospital).
Requests for Single Reprints: Nancy R. Cook, ScD, Division of Preventive Medicine, Brigham and Women's Hospital, 900 Commonwealth Avenue East, Boston, MA 02215; e-mail, email@example.com.
Current Author Addresses: Drs. Cook and Ridker: Division of Preventive Medicine, Brigham and Women's Hospital, 900 Commonwealth Avenue East, Boston, MA 02215.
Author Contributions: Conception and design: N.R. Cook, P.M Ridker.
Analysis and interpretation of the data: N.R. Cook, P.M Ridker.
Drafting of the article: N.R. Cook.
Critical revision of the article for important intellectual content: N.R. Cook, P.M Ridker.
Final approval of the article: N.R. Cook, P.M Ridker.
Provision of study materials or patients: P.M Ridker.
Statistical expertise: N.R. Cook.
Administrative, technical, or logistic support: N.R. Cook, P.M Ridker.
Collection and assembly of data: P.M Ridker.
Models for risk prediction are widely used in clinical practice to stratify risk and assign treatment strategies. The contribution of new biomarkers has largely been based on the area under the receiver-operating characteristic curve, but this measure can be insensitive to important changes in absolute risk. Methods based on risk stratification have recently been proposed to compare predictive models. Such methods include the reclassification calibration statistic, the net reclassification improvement, and the integrated discrimination improvement. This article demonstrates the use of reclassification measures and illustrates their performance for well-known cardiovascular risk predictors in a cohort of women. These measures are targeted at evaluating the potential of new models and markers to change risk strata and alter treatment decisions.
Nancy R. Cook, Paul M Ridker. Advances in Measuring the Effect of Individual Predictors of Cardiovascular Risk: The Role of Reclassification Measures. Ann Intern Med. 2009;150:795–802. doi: 10.7326/0003-4819-150-11-200906020-00007
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Published: Ann Intern Med. 2009;150(11):795-802.
Cardiology, Coronary Risk Factors, Prevention/Screening.
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Print ISSN: 0003-4819 | Online ISSN: 1539-3704
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