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Cited by 7,491Health Promotion and Cardiovascular PreventionCardiovascular Health and Risk FactorsLipoproteins and Cardiovascular Health

General Cardiovascular Risk Profile for Use in Primary Care: The Framingham Heart Study

Open access
D’Agostino, Ralph B., Vasan, Ramachandran S., Pencina, Michael J., Wolf, Philip A., Cobain, Mark, Massaro, Joseph M., Kannel, William B.·2008·Circulation
DOI 10.1161/circulationaha.107.699579
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Abstract

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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Crossref · 10.1161/circulationaha.107.699579

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  • The predicted 10-year CVD risk score was calculated using BMI-based sex-specific risk equations developed from the Framingham Heart Study by D'Agostino et al.

    “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: <i>post-hoc</i> analysis of the SURMOUNT-5 trial (2025) · cites this paper as [15]

  • The CAC score was measured manually by expert readers using the method by Agatston and Janowitz on dedicated workstations, as reported in the parent FHS, PROMISE, and ROMICAT-II studies.

    “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]

    The Measurement of CVD Risk Factors section describes blood pressure, cholesterol, smoking, and diabetes measurements, but not CAC scoring. Searches for Agatston and Janowitz, expert readers, dedicated workstations, PROMISE, and ROMICAT-II found no passage addressing the claimed measurement method. Page numbers were not available for these passages. (LLM, conf=0.76)

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  • Many cardiovascular risk assessment systems are available and have been comprehensively reviewed, including Framingham models, SCORE, ASSIGN, Q-Risk, PROCAM, Reynolds, CUORE, the Pooled Cohort equations, and Globorisk.

    “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]

  • 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 women.

    “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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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)
ORCID
Venue
Circulation
Publisher
Ovid Technologies (Wolters Kluwer Health)
Published
2008-02-12
Volume
117
Issue
6
Pages
743-753
ISSN
  • 0009-7322 (ISSN-L)
  • 1524-4539
DOI
10.1161/circulationaha.107.699579
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
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 › Surgery › 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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