The DOI matches its Crossref record; 49 of the 50 references it cites were found in a registry or an index.
The Effect of Including C-Reactive Protein in Cardiovascular Risk Prediction Models for Women
Abstract
BACKGROUND: While high-sensitivity C-reactive protein (hsCRP) is an independent predictor of cardiovascular risk, global risk prediction models incorporating hsCRP have not been developed for clinical use. OBJECTIVE: To develop and compare global cardiovascular risk prediction models with and without hsCRP. DESIGN: Observational cohort study. SETTING: U.S. female health professionals. PARTICIPANTS: Initially healthy nondiabetic women age 45 years and older participating in the Women's Health Study and followed an average of 10 years. MEASUREMENTS: Incident cardiovascular events (myocardial infarction, stroke, coronary revascularization, and cardiovascular death). RESULTS: High-sensitivity CRP made a relative contribution to global risk at least as large as that provided by total, high-density lipoprotein (HDL), and low-density lipoprotein (LDL) cholesterol individually, but less than that provided by age, smoking, and blood pressure. All global measures of fit improved when hsCRP was included, with likelihood-based measures demonstrating strong preference for models that include hsCRP. With use of 10-year risk categories of 0% to less than 5%, 5% to less than 10%, 10% to less than 20%, and 20% or greater, risk prediction was more accurate in models that included hsCRP, particularly for risk between 5% and 20%. Among women initially classified with risks of 5% to less than 10% and 10% to less than 20% according to the Adult Treatment Panel III covariables, 21% and 19%, respectively, were reclassified into more accurate risk categories. Although addition of hsCRP had minimal effect on the c-statistic (a measure of model discrimination) once age, smoking, and blood pressure were accounted for, the effect was nonetheless greater than that of total, LDL, or HDL cholesterol, suggesting that the c-statistic may be insensitive in evaluating risk prediction models. LIMITATIONS: Data were available only for women. CONCLUSIONS: A global risk prediction model that includes hsCRP improves cardiovascular risk classification in women, particularly among those with a 10-year risk of 5% to 20%. In models that include age, blood pressure, and smoking status, hsCRP improves prediction at least as much as do lipid measures.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“CRP has emerged as a particularly stronger independent risk factor for cardiovascular disease than the low-density lipoprotein cholesterol level [13, 33, 34].”
From Exercise as a Mean to Control Low‐Grade Systemic Inflammation (2008) · cites this paper as [33]
Citations
Cites
An Introduction to the Bootstrap
Efron, B., & Tibshirani, R. J. (1994) · doi:10.1201/9780429246593 · Cited by 40,500
Regression Models and Life-Tables
Cox, D. R. (1972) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1972.tb00899.x · Cited by 39,793
Grundy, S. M., Bilheimer, D. W., Chait, A., Clark, L. T., Denke, M. A., Havel, R. J., Hazzard, W. R., Hulley, S. B., Hunninghake, D. B., Kreisberg, R. A., et al. (1993) · JAMA · doi:10.1001/jama.269.23.3015 · Cited by 27,944
Regression Models and Life-Tables
Cox, D. R. (1992) · Springer Series in Statistics · doi:10.1007/978-1-4612-4380-9_37 · Cited by 26,297
Expert Panel on Detection, E. (2001) · JAMA: The Journal of the American Medical Association · doi:10.1001/jama.285.19.2486 · Cited by 26,011
The Elements of Statistical Learning
Hastie, T., Tibshirani, R., & Friedman, J. (2009) · Springer Series in Statistics · doi:10.1007/978-0-387-84858-7 · Cited by 25,970
The meaning and use of the area under a receiver operating characteristic (ROC) curve.
Hanley, J. A., & McNeil, B. J. (1982) · Radiology · doi:10.1148/radiology.143.1.7063747 · Cited by 21,856
Prediction of coronary heart disease using risk factor categories
Wilson, P. W. F., D’Agostino, R. B., Levy, D., Belanger, A. M., Silbershatz, H., & Kannel, W. B. (1998) · Circulation · doi:10.1161/01.cir.97.18.1837 · Cited by 9,581
Harrell (2015) · Springer Series in Statistics · doi:10.1007/978-3-319-19425-7 · Cited by 6,878
Pearson, T. A., Mensah, G. A., Alexander, R. W., Anderson, J. L., Cannon, R. O., Criqui, M., Fadl, Y. Y., Fortmann, S. P., Hong, Y., Myers, G. L., et al. (2003) · Circulation · doi:10.1161/01.cir.0000052939.59093.45 · Cited by 6,401
A note on a general definition of the coefficient of determination
NAGELKERKE, N. J. D. (1991) · Biometrika · doi:10.1093/biomet/78.3.691 · Cited by 5,927
Inflammation, aspirin, and the risk of cardiovascular disease in apparently healthy men
Ridker, P. M., Cushman, M., Stampfer, M. J., Tracy, R. P., & Hennekens, C. H. (1997) · New England Journal of Medicine · doi:10.1056/nejm199704033361401 · Cited by 5,504
C-Reactive Protein, Interleukin 6, and Risk of Developing Type 2 Diabetes Mellitus
Pradhan, A. D. (2001) · JAMA · doi:10.1001/jama.286.3.327 · Cited by 4,433
Model Selection and Inference: A Practical Information-Theoretic Approach
Strawderman, R. L., Burnham, K. P., & Anderson, D. R. (2000) · Journal of the American Statistical Association · doi:10.2307/2669574 · Cited by 4,194
Statistical Methods for Rates and Proportions, 2nd ed
GROVE, W. A. (1981) · American Journal of Psychiatry · doi:10.1176/ajp.138.12.1644-a · Cited by 3,756
Ridker, P. M., Rifai, N., Rose, L., Buring, J. E., & Cook, N. R. (2002) · New England Journal of Medicine · doi:10.1056/nejmoa021993 · Cited by 3,604
Danesh, J., Wheeler, J. G., Hirschfield, G. M., Eda, S., Eiriksdottir, G., Rumley, A., Lowe, G. D. O., Pepys, M. B., & Gudnason, V. (2004) · New England Journal of Medicine · doi:10.1056/nejmoa032804 · Cited by 2,953
Chronic Subclinical Inflammation as Part of the Insulin Resistance Syndrome
Festa, A., D’Agostino, R., Howard, G., Mykkänen, L., Tracy, R. P., & Haffner, S. M. (2000) · Circulation · doi:10.1161/01.cir.102.1.42 · Cited by 2,366
C-Reactive Protein Levels and Outcomes after Statin Therapy
Ridker, P. M., Cannon, C. P., Morrow, D., Rifai, N., Rose, L. M., McCabe, C. H., Pfeffer, M. A., & Braunwald, E. (2005) · New England Journal of Medicine · doi:10.1056/nejmoa042378 · Cited by 2,292
Ridker, P. M., Buring, J. E., Cook, N. R., & Rifai, N. (2003) · Circulation · doi:10.1161/01.cir.0000055014.62083.05 · Cited by 2,292
D'Agostino, R. B., Grundy, S., Sullivan, L. M., Wilson, P., & for the CHD Risk Prediction Group (2001) · JAMA · doi:10.1001/jama.286.2.180 · Cited by 2,108
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-citationPresentation of multivariate data for clinical use: The Framingham Study risk score functions
SULLIVAN, L. M., Massaro, J. M., & D’Agostino, R. B. (2004) · Statistics in Medicine · doi:10.1002/sim.1742 · Cited by 1,756
Ridker, P. M., Rifai, N., Clearfield, M., Downs, J. R., Weis, S. E., Miles, J. S., & Gotto, A. M. (2001) · New England Journal of Medicine · doi:10.1056/nejm200106283442601 · Cited by 1,557
Prevalence of Conventional Risk Factors in Patients With Coronary Heart Disease
Khot, U. N. (2003) · JAMA · doi:10.1001/jama.290.7.898 · Cited by 1,494
Ridker, P. M., Rifai, N., Pfeffer, M. A., Sacks, F. M., Moye, L. A., Goldman, S., Flaker, G. C., & Braunwald, E. (1998) · Circulation · doi:10.1161/01.cir.98.9.839 · Cited by 1,389
Statin Therapy, LDL Cholesterol, C-Reactive Protein, and Coronary Artery Disease
Nissen, S. E., Tuzcu, E. M., Schoenhagen, P., Crowe, T., Sasiela, W. J., Tsai, J., Orazem, J., Magorien, R. D., O'Shaughnessy, C., & Ganz, P. (2005) · New England Journal of Medicine · doi:10.1056/nejmoa042000 · Cited by 1,325
Inflammatory Markers and the Risk of Coronary Heart Disease in Men and Women
Pai, J. K., Pischon, T., Ma, J., Manson, J. E., Hankinson, S. E., JOSHIPURA, K. J., Curhan, G. C., Rifai, N., Cannuscio, C. C., Stampfer, M. J., et al. (2004) · New England Journal of Medicine · doi:10.1056/nejmoa040967 · Cited by 1,186
Festa, A., D’Agostino, R., Tracy, R. P., & Haffner, S. M. (2002) · Diabetes · doi:10.2337/diabetes.51.4.1131 · Cited by 1,057
Major Risk Factors as Antecedents of Fatal and Nonfatal Coronary Heart Disease Events
Greenland, P. (2003) · JAMA · doi:10.1001/jama.290.7.891 · Cited by 1,053
Ridker, P. M., Rifai, N., & Clearfield, M. B. (2001) · ACC Current Journal Review · doi:10.1016/s1062-1458(01)00460-3 · Cited by 760
Ridker, P. M., Rifai, N., Cook, N. R., Bradwin, G., & Buring, J. E. (2005) · JAMA · doi:10.1001/jama.294.3.326 · Cited by 744
Ridker, P. M., Wilson, P. W. F., & Grundy, S. M. (2004) · Circulation · doi:10.1161/01.cir.0000132467.45278.59 · Cited by 645
Ballantyne, C. M., Hoogeveen, R. C., Bang, H., Coresh, J., Folsom, A. R., HEISS, G. M., & Sharrett, A. R. (2004) · Circulation · doi:10.1161/01.cir.0000116763.91992.f1 · Cited by 611
Improving Coronary Heart Disease Risk Assessment in Asymptomatic People
Greenland, P., Smith, S. C., & Grundy, S. M. (2001) · Circulation · doi:10.1161/hc4201.097189 · Cited by 558
A new measure of prognostic separation in survival data
Royston, P., & Sauerbrei, W. (2004) · Statistics in Medicine · doi:10.1002/sim.1621 · Cited by 450 · cited 2×
“We computed the D-statistic of Royston and Sauerbrei (35), based on the separation of survival curves by predictor variables, and again adjusted for optimism.”
MethodC-Reactive Protein Modulates Risk Prediction Based on the Framingham Score
Köenig, W., Löwel, H., Baumert, J. J., & Meisinger, C. (2004) · Circulation · doi:10.1161/01.cir.0000120707.98922.e3 · Cited by 440
Established and Emerging Plasma Biomarkers in the Prediction of First Atherothrombotic Events
Ridker, P. M., Brown, N. J., Vaughan, D. E., Harrison, D. G., & Mehta, J. L. (2004) · Circulation · doi:10.1161/01.cir.0000133444.17867.56 · Cited by 420
Cushman, M., Arnold, A. M., Psaty, B. M., Manolio, T. A., Kuller, L. H., Burke, G. L., Polak, J. F., & Tracy, R. P. (2005) · Circulation · doi:10.1161/circulationaha.104.504159 · Cited by 368
Baseline Characteristics of Participants in the Women's Health Study
Rexrode, K. M., Lee, I.-M. M., Cook, N. R., Hennekens, C. H., & Buring, J. E. (2000) · Journal of Women s Health & Gender-Based Medicine · doi:10.1089/152460900318911 · Cited by 308
On criteria for evaluating models of absolute risk
Gail, M. H. (2005) · Biostatistics · doi:10.1093/biostatistics/kxi005 · Cited by 230
Boekholdt, S. M., Hack, C. E., Sandhu, M. S., Luben, R., Bingham, S. A., Wareham, N. J., Peters, R. J. G., Jukema, J. W., Day, N., Kastelein, J. J. P., et al. (2005) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2005.09.023 · Cited by 177
Sensitivity and Specificity should be De-emphasized in Diagnostic Accuracy Studies
Moons, K. G. M., & Harrell, F. E. (2003) · Academic Radiology · doi:10.1016/s1076-6332(03)80087-9 · Cited by 100
Laaksonen, D. E., NISKANEN, L. K., Nyyssönen, K., Punnonen, K. R. A., Tuomainen, T., & Salonen, J. T. (2005) · European Heart Journal · doi:10.1093/eurheartj/ehi237 · Cited by 84
Grundy, S. M. (2005) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2005.05.007 · Cited by 46
Kent, S. M., & Taylor, A. J. (2003) · The American Journal of Cardiology · doi:10.1016/j.amjcard.2003.07.040 · Cited by 18
Statistics in the medical literature: 3
Altman, D. G. (1999) · Statistics in Medicine · doi:10.1002/(sici)1097-0258(19990228)18:4 · Cited by 17
Harrell, F., Jr. (1996) · doi:10.1002/(sici)1097-0258(19960229)15:4
Hosmer (1997) · doi:10.1002/(sici)1097-0258(19970515)16:9
Research works printed but not linked: 3
- Buring JE, 1992, Journal of Myocardial Ischemia, 4, 27
- Nagelkerke NJ, 1991, Biomka, 78, 691
- Boekholdt SM, 2005, Atherosclerosis
Cited by
Sorted by citations
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
Use and Misuse of the Receiver Operating Characteristic Curve in Risk Prediction
Cook, N. R. (2007) · Circulation · doi:10.1161/circulationaha.106.672402 · Cited by 2,167
2010 ACCF/AHA Guideline for Assessment of Cardiovascular Risk in Asymptomatic Adults
Greenland, P., Alpert, J. S., Beller, G. A., Benjamin, E. J., Budoff, M. J., Fayad, Z. A., Foster, E., Hlatky, M. A., Hodgson, J. M., Kushner, F. G., et al. (2010) · Circulation · doi:10.1161/cir.0b013e3182051b4c · Cited by 1,976
Ridker, P. M., Buring, J. E., Rifai, N., & Cook, N. R. (2007) · JAMA · doi:10.1001/jama.297.6.611 · Cited by 1,814
2010 ACCF/AHA Guideline for Assessment of Cardiovascular Risk in Asymptomatic Adults
Greenland, P., Alpert, J. S., Beller, G. A., Benjamin, E. J., Budoff, M. J., Fayad, Z. A., Foster, E., Hlatky, M. A., Hodgson, J. M., Kushner, F. G., et al. (2010) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2010.09.001 · Cited by 1,348
Metadata
- Authors
- Cook, N. R., Buring, J. E., & Ridker, P. M.
- Affiliations
- Brigham and Women's Hospital (US)
- Venue
- Annals of Internal Medicine
- Publisher
- American College of Physicians
- Published
- 2006-07-04
- Volume
- 145
- Issue
- 1
- Pages
- 21-29
- ISSN
- 0003-4819 (ISSN-L)
- 1539-3704
- OpenAlex
- W2100083473
- Cited by
- 504
- References
- 50
- Citations by year
- 2026: 2 · 2025: 7 · 2024: 8 · 2023: 10 · 2022: 9 · 2021: 11 · 2020: 7 · 2019: 13 · 2018: 14 · 2017: 9 · 2016: 19 · 2015: 23 · 2014: 21 · 2013: 31 · 2012: 35
- FWCI
- 58.97
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Annals of Internal Medicine (publishedVersion)
- PubMed (publishedVersion)
- UCLA - Biblioteca de Ciencias de la Salud (submittedVersion)
- Funders
- National Institutes of Health (5r01hl043851-10)
- National Heart, Lung, and Blood Institute (HL43851)
- National Cancer Institute (CA-47988, R01CA047988)
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Lipoproteins and Cardiovascular Health
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Health Promotion and Cardiovascular Prevention
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Health and Risk Factors
- Keywords
- high-sensitivity C-reactive protein, cardiovascular risk prediction, women, 10-year cardiovascular risk, risk reclassification, model discrimination, concordance index, myocardial infarction, stroke, cardiovascular mortality, Women's Health Study
- MeSH terms
- Age Factors, Blood Pressure, C-Reactive Protein, Cardiovascular Diseases, Female, Humans, Lipids, Middle Aged, Smoking, United States, Cohort Studies, Biomarkers, Proportional Hazards Models, Risk Assessment
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review