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General Cardiovascular Risk Profile for Use in Primary Care: The Framingham Heart Study
Open accessAbstract
Background— Separate multivariable risk algorithms are commonly used to assess risk of specific atherosclerotic cardiovascular disease (CVD) events, ie, coronary heart disease, cerebrovascular disease, peripheral vascular disease, and heart failure. The present report presents a single multivariable risk function that predicts risk of developing all CVD and of its constituents. Methods and Results— We used Cox proportional-hazards regression to evaluate the risk of developing a first CVD event in 8491 Framingham study participants (mean age, 49 years; 4522 women) who attended a routine examination between 30 and 74 years of age and were free of CVD. Sex-specific multivariable risk functions (“general CVD” algorithms) were derived that incorporated age, total and high-density lipoprotein cholesterol, systolic blood pressure, treatment for hypertension, smoking, and diabetes status. We assessed the performance of the general CVD algorithms for predicting individual CVD events (coronary heart disease, stroke, peripheral artery disease, or heart failure). Over 12 years of follow-up, 1174 participants (456 women) developed a first CVD event. All traditional risk factors evaluated predicted CVD risk (multivariable-adjusted P <0.0001). The general CVD algorithm demonstrated good discrimination (C statistic, 0.763 [men] and 0.793 [women]) and calibration. Simple adjustments to the general CVD risk algorithms allowed estimation of the risks of each CVD component. Two simple risk scores are presented, 1 based on all traditional risk factors and the other based on non–laboratory-based predictors. Conclusions— A sex-specific multivariable risk factor algorithm can be conveniently used to assess general CVD risk and risk of individual CVD events (coronary, cerebrovascular, and peripheral arterial disease and heart failure). The estimated absolute CVD event rates can be used to quantify risk and to guide preventive care.
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“The predicted 10-year CVD risk score was calculated using the BMI-based sex-specific risk equations (supplementary material online, Methods), which were developed from the Framingham Heart Study by D’Agostino et al.15”
From Tirzepatide compared with semaglutide and 10-year cardiovascular disease risk reduction in obesity: post-hoc analysis of the SURMOUNT-5 trial (2025) · cites this paper as [15]
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In the citing paper
“The CAC score was measured manually by expert readers using the method by Agatston and Janowitz5,6 on dedicated workstations, as reported in the parent FHS17, PROMISE19, and ROMICAT-II20 studies.”
From Deep convolutional neural networks to predict cardiovascular risk from computed tomography (2021) · cites this paper as [17]
Experimental — accuracy not yet measuredIn the citing paper
“Many risk assessment systems are available and have been comprehensively reviewed, including different Framingham models, 41 Systemic Coronary Risk Estimation (SCORE), 42 ASSIGN (CV risk estimation model from the Scottish Intercollegiate Guidelines Network), 43 Q-Risk, 44 Prospective Cardiovascular Munster Study (PROCAM), 45 Reynolds, 46,47 CUORE, 48 the Pooled Cohort equations 49 and Globorisk. 5”
From 2016 ESC/EAS Guidelines for the Management of Dyslipidaemias (2016) · cites this paper as [41]
In the citing paper
“According to a recent large-scale cross-sectional study conducted in Japan on visceral fat area and accumulated risk factors, the average number of obesity-related cardiovascular risk factors (dyslipidemia, high blood pressure, and high blood glucose) was more than 1.0 at 100 cm2 for visceral fat area in both men and women330).”
From Japan Atherosclerosis Society (JAS) guidelines for prevention of atherosclerotic cardiovascular diseases 2017 (2018) · cites this paper as [330]
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Citations
Cites
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
Yusuf, S., Hawken, S., Ôunpuu, S., Dans, T., Avezum, A., Lanas, F., McQueen, M., Budaj, A., Pais, P., Varigos, J., et al. (2004) · The Lancet · doi:10.1016/s0140-6736(04)17018-9 · Cited by 12,026
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
Self-citationPencina, 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
Self-citationLopez, A. D., Mathers, C. D., Ezzati, M., Jamison, D. T., & Murray, C. J. (2006) · The Lancet · doi:10.1016/s0140-6736(06)68770-9 · Cited by 5,630
Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project
Conroy, R. (2003) · European Heart Journal · doi:10.1016/s0195-668x(03)00114-3 · Cited by 5,290
Rosamond, W., Flegal, K., Friday, G., Furie, K., Go, A., Greenlund, K., Haase, N., Ho, M., Howard, V., Kissela, B., et al. (2007) · Circulation · doi:10.1161/circulationaha.106.179918 · Cited by 3,277
De Backer, G. (2003) · European Heart Journal · doi:10.1016/s0195-668x(03)00347-6 · Cited by 2,251
Cardiovascular disease risk profiles
Anderson, K. M., Odell, P. M., Wilson, P. W. F., & Kannel, W. B. (1991) · American Heart Journal · doi:10.1016/0002-8703(91)90861-b · Cited by 2,163
Self-citationEpidemiological approaches to heart disease: the Framingham study
Dawber, T. R., Meadors, G. F., & Moore, F. E. (1951) · American Journal of Public Health and the Nations Health · doi:10.2105/ajph.41.3.279 · Cited by 2,148
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
Self-citationAn updated coronary risk profile. A statement for health professionals.
Anderson, K. M., Wilson, P. W., Odell, P. M., & Kannel, W. B. (1991) · Circulation · doi:10.1161/01.cir.83.1.356 · Cited by 1,834
Self-citationRidker, P. M., Buring, J. E., Rifai, N., & Cook, N. R. (2007) · JAMA · doi:10.1001/jama.297.6.611 · Cited by 1,814
Probability of stroke: a risk profile from the Framingham Study.
Wolf, P. A., D'Agostino, R. B., Belanger, A. J., & Kannel, W. B. (1991) · Stroke · doi:10.1161/01.str.22.3.312 · Cited by 1,782
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
Self-citationAN INVESTIGATION OF CORONARY HEART DISEASE IN FAMILIES
Kannel, W. B., Feinleib, M., McNAMARA, P. M., Garrison, R. J., & Castelli, W. P. (1979) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a112813 · Cited by 1,639
Self-citationAssmann, G., Cullen, P., & Schulte, H. (2002) · Circulation · doi:10.1161/hc0302.102575 · Cited by 1,541
Pencina, M. J., & D’Agostino, R. B. (2004) · Statistics in Medicine · doi:10.1002/sim.1802 · Cited by 1,442
Self-citationGreenland, P. (2007) · Statistics in Medicine · doi:10.1002/sim.2976 · Cited by 1,300
Prediction of lifetime risk for cardiovascular disease by risk factor burden at 50 years of age
Lloyd-Jones, D. M., Leip, E. P., Larson, M. G., D’Agostino, R. B., Beiser, A., Wilson, P. W. F., Wolf, P. A., & Levy, D. (2006) · Circulation · doi:10.1161/circulationaha.105.548206 · Cited by 1,298
Self-citationPrepared, B. (2005) · Heart · doi:10.1136/hrt.2005.079988 · Cited by 1,223
A general cardiovascular risk profile: The Framingham study
Kannel, W. B., McGee, D., & Gordon, T. (1976) · The American Journal of Cardiology · doi:10.1016/0002-9149(76)90061-8 · Cited by 1,189
Self-citationHippisley-Cox, J., Coupland, C., Vinogradova, Y., Robson, J., May, M., & Brindle, P. (2007) · British medical journal · doi:10.1136/bmj.39261.471806.55 · Cited by 1,070
Intermittent Claudication: A Risk Profile From The Framingham Heart Study
Murabito, J. M., D’Agostino, R. B., Silbershatz, H., & Wilson, P. W. F. (1997) · Circulation · doi:10.1161/01.cir.96.1.44 · Cited by 696
Self-citationWoodward, M., Brindle, P., & Tunstall-Pedoe, H. (2007) · Heart · doi:10.1136/hrt.2006.108167 · Cited by 667
Wannamethee, S. G., Shaper, A. G., LENNON, L. T., & Morris, R. W. (2005) · Archives of Internal Medicine · doi:10.1001/archinte.165.22.2644 · Cited by 667
Jackson, R., Lawes, C. M. M., Bennett, D., Milne, R. J., & Rodgers, A. (2005) · The Lancet · doi:10.1016/s0140-6736(05)17833-7 · Cited by 521
Brindle, P., Beswick, A. D., Fahey, T. P., & Ebrahim, S. B. J. (2006) · Heart · doi:10.1136/hrt.2006.087932 · Cited by 450
Profile for Estimating Risk of Heart Failure
Kannel, W. B., D’Agostino, R. B., Silbershatz, H., Belanger, A. J., Wilson, P. W. F., & Levy, D. A. (1999) · Archives of Internal Medicine · doi:10.1001/archinte.159.11.1197 · Cited by 428
Self-citationAn adaptation of the Framingham coronary heart disease risk function to European Mediterranean areas
Marrugat, J., D’Agostino, R. B., SULLIVAN, L. M., Elosúa, R., Wilson, P., Ordovás, J. M., Solanas, P., Cordón, F., Ramos, R., Sala, J., et al. (2003) · Journal of Epidemiology & Community Health · doi:10.1136/jech.57.8.634 · Cited by 371
Self-citationEvaluation of the Performance of Survival Analysis Models: Discrimination and Calibration Measures
D’Agostino, R. B., & Nam, B. (2003) · Handbook of statistics · doi:10.1016/s0169-7161(03)23001-7 · Cited by 340
Self-citationPrimary Prevention of Coronary Heart Disease
Grundy, S. M. (1999) · Circulation · doi:10.1161/01.cir.100.9.988 · Cited by 266
Califf, R. M., Armstrong, P. W., Carver, J. R., D’Agostino, R. B., & Strauss, W. (1996) · Journal of the American College of Cardiology · doi:10.1016/0735-1097(96)87733-3 · Cited by 257
Self-citationUpdated New Zealand cardiovascular disease risk-benefit prediction guide
Jackson, R. (2000) · BMJ · doi:10.1136/bmj.320.7236.709 · Cited by 229
Ferrario, M., Chiodini, P., Chambless, L. E., Cesana, G., Vanuzzo, D., Panico, S., Sega, R., Pilotto, L., Palmieri, L., & Giampaoli, S. (2005) · International Journal of Epidemiology · doi:10.1093/ije/dyh405 · Cited by 214
Statins for heart failure: at the crossroads between cholesterol reduction and pleiotropism?
von Haehling, S., & Anker, S. D. (2004) · Heart · doi:10.1136/hrt.2004.042515 · Cited by 201
Concept and usefulness of cardiovascular risk profiles
Kannel, W. B., D’Agostino, R. B., SULLIVAN, L. M., & Wilson, P. W. F. (2004) · American Heart Journal · doi:10.1016/j.ahj.2003.10.022 · Cited by 151
Self-citationTask force 6. Cost effectiveness of assessment and management of risk factors
Goldman, L., Garber, A. M., Grover, S. A., & Hlatky, M. A. (1996) · Journal of the American College of Cardiology · doi:10.1016/0735-1097(96)87734-5 · Cited by 110
A risk score predicted coronary heart disease and stroke in a Chinese cohort
Zhang, X.-F., Attia, J., D’Este, C. A., Yu, X.-H., & Wu, X. (2005) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2005.01.013 · Cited by 85
Inference on Correlated Discrimination Measures in Survival Analysis: A Nonparametric Approach
Antolini, L., Nam, B., & D’Agostino, R. B. (2004) · Communication in Statistics- Theory and Methods · doi:10.1081/sta-200026579 · Cited by 69
Self-citationChang, M., Hahn, R. A., Teutsch, S. M., & Hutwagner, L. (2001) · Journal of Clinical Epidemiology · doi:10.1016/s0895-4356(00)00343-7 · Cited by 69
Cupples, L. A. (1987) · Medical Entomology and Zoology · Cited by 64
Risk scoring in the assessment of cardiovascular risk
Beswick, A. D., & Brindle, P. M. (2006) · Current Opinion in Lipidology · doi:10.1097/01.mol.0000236362.56216.44 · Cited by 59
Menotti, A., Lanti, M., Agabiti‐Rosei, E., Carratelli, L., Cavera, G., Dormi, A., Gaddi, A. V., Mancini, M., Motolese, M., Muiesan, M. L., et al. (2005) · Nutrition Metabolism and Cardiovascular Diseases · doi:10.1016/j.numecd.2005.07.007 · Cited by 50
Task force 4. Efficacy of risk factor management
Forrester, J. S., Merz, C. N. B., Bush, T. L., Cohn, J. N., Hunninghake, D. B., Parthasarathy, S., & Superko, H. R. (1996) · Journal of the American College of Cardiology · doi:10.1016/0735-1097(96)87732-1 · Cited by 50
Task force 2. Clinical epidemiology: The conceptual basis for interpreting risk factors
Furberg, C. D., Hennekens, C. H., Hulley, S. B., Manolio, T. A., Psaty, B. M., & Whelton, P. K. (1996) · Journal of the American College of Cardiology · doi:10.1016/0735-1097(96)87730-8 · Cited by 21
Notarbartolo, A., Menotti, A., Lanti, M., Agabiti‐Rosei, E., Carratelli, L., Cavera, G., Dormi, A., Gaddi, A. V., Mancini, M., Motolese, M., et al. (2005) · Cited by 12
Harrell, F., Jr. (1996) · doi:10.1002/(sici)1097-0258(19960229)15:4
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Metadata
- Authors
- D’Agostino, R. B., Vasan, R. S., Pencina, M. J., Wolf, P. A., Cobain, M., Massaro, J. M., & Kannel, W. B.
- Affiliations
- Boston University (US)
- Venue
- Circulation
- Published
- 2008-02-12
- Volume
- 117
- Issue
- 6
- Pages
- 743-753
- ISSN
- 0009-7322 (ISSN-L)
- 1524-4539
- OpenAlex
- W2148092884
- Cited by
- 7,491
- References
- 52
- Citations by year
- 2026: 491 · 2025: 567 · 2024: 552 · 2023: 511 · 2022: 529 · 2021: 592 · 2020: 562 · 2019: 454 · 2018: 475 · 2017: 452 · 2016: 385 · 2015: 389 · 2014: 391 · 2013: 323 · 2012: 294
- FWCI
- 169.19
- Type
- journal article
- Language
- en
- Update notices
- correction (2008-07-22)
- Open access
- bronze
- doi.org
- Locations
- Circulation (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (n01hc25195-41-0-1)
- National Heart, Lung, and Blood Institute (2K24 HL 04334, N01‐HC25195, K24HL004334)
- Topics
- 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
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Lipoproteins and Cardiovascular Health
- Keywords
- cardiovascular risk prediction, atherosclerotic cardiovascular disease, Framingham risk score, coronary artery disease, stroke, peripheral arterial disease, heart failure, traditional risk factors, cholesterol, blood pressure, smoking, diabetes mellitus, primary care
- MeSH terms
- Adult, Aged, Algorithms, Cardiovascular Diseases, Female, Humans, Longitudinal Studies, Male, Middle Aged, Primary Health Care, Risk Factors, Sex Factors, Multivariate Analysis, Proportional Hazards Models, Risk Assessment
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