The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Use and Misuse of the Receiver Operating Characteristic Curve in Risk Prediction
Open accessAbstract
The c statistic, or area under the receiver operating characteristic (ROC) curve, achieved popularity in diagnostic testing, in which the test characteristics of sensitivity and specificity are relevant to discriminating diseased versus nondiseased patients. The c statistic, however, may not be optimal in assessing models that predict future risk or stratify individuals into risk categories. In this setting, calibration is as important to the accurate assessment of risk. For example, a biomarker with an odds ratio of 3 may have little effect on the c statistic, yet an increased level could shift estimated 10-year cardiovascular risk for an individual patient from 8% to 24%, which would lead to different treatment recommendations under current Adult Treatment Panel III guidelines. Accepted risk factors such as lipids, hypertension, and smoking have only marginal impact on the c statistic individually yet lead to more accurate reclassification of large proportions of patients into higher-risk or lower-risk categories. Perfectly calibrated models for complex disease can, in fact, only achieve values for the c statistic well below the theoretical maximum of 1. Use of the c statistic for model selection could thus naively eliminate established risk factors from cardiovascular risk prediction scores. As novel risk factors are discovered, sole reliance on the c statistic to evaluate their utility as risk predictors thus seems ill-advised.
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Citations
Cites
Prediction of coronary heart disease using risk factor categories
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Sick individuals and sick populations
Rose, G. (2001) · International Journal of Epidemiology · doi:10.1093/ije/30.3.427 · Cited by 3,736
Sick individuals and sick populations
ROSE, G. (1985) · International Journal of Epidemiology · doi:10.1093/ije/14.1.32 · Cited by 2,701
A Randomized Trial of Low-Dose Aspirin in the Primary Prevention of Cardiovascular Disease in Women
Ridker, P. M., Cook, N. R., Lee, I.-M., Gordon, D., Gaziano, J. M., Manson, J. E., Hennekens, C. H., & Buring, J. E. (2005) · New England Journal of Medicine · doi:10.1056/nejmoa050613 · Cited by 1,945
Self-citationThe effect of including C-reactive protein in cardiovascular risk prediction models for women
Cook, N. R., Buring, J. E., & Ridker, P. M. (2006) · Annals of Internal Medicine · doi:10.7326/0003-4819-145-1-200607040-00128 · Cited by 504
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Cited by
Pencina, M. J., D' Agostino, R. B., D' Agostino, R. B., & Vasan, R. S. (2008) · Statistics in Medicine · doi:10.1002/sim.2929 · Cited by 6,493
Brook, R. D., Rajagopalan, S., Pope, C. A., Brook, J. R., Bhatnagar, A., Diez-Roux, A. V., Holguin, F., Hong, Y., Luepker, R. V., Mittleman, M. A., et al. (2010) · Circulation · doi:10.1161/cir.0b013e3181dbece1 · Cited by 6,548
Assessing the Performance of Prediction Models: A Framework for Traditional and Novel Measures
Steyerberg, E. W., Vickers, A. J., Cook, N. R., Gerds, T., Gonen, M., Obuchowski, N., Pencina, M. J., & Kattan, M. W. (2010) · Epidemiology · doi:10.1097/ede.0b013e3181c30fb2 · Cited by 5,170
Self-citationMoons, K. G. M., Altman, D. G., Reitsma, J. B., Ioannidis, J. P. A., Macaskill, P., Steyerberg, E. W., Vickers, A. J., Ransohoff, D. F., & Collins, G. S. (2015) · Annals of Internal Medicine · doi:10.7326/m14-0698 · Cited by 5,147
Arterial Stiffness and Cardiovascular Events: The Framingham Heart Study
Mitchell, G. F., Hwang, S.-J., Vasan, R. S., Larson, M. G., Pencina, M. J., Hamburg, N. M., Vita, J. A., Levy, D., & Benjamin, E. J. (2010) · Circulation · doi:10.1161/circulationaha.109.886655 · Cited by 2,225
Metadata
- Authors
- Cook, N. R.
- Venue
- Circulation
- Published
- 2007-02-20
- Volume
- 115
- Issue
- 7
- Pages
- 928-935
- ISSN
- 0009-7322 (ISSN-L)
- 1524-4539
- OpenAlex
- W2157995113
- Cited by
- 2,112
- References
- 6
- FWCI
- 109.62
- Type
- journal article
- Language
- en
- Open access
- bronze
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