Cited by 287Cardiovascular Health and Risk FactorsHealth Promotion and Cardiovascular PreventionLipoproteins and Cardiovascular Health

A novel risk score to predict cardiovascular disease risk in national populations (Globorisk): a pooled analysis of prospective cohorts and health examination surveys

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Hajifathalian, Kaveh, Ueda, Peter, Lu, Yuan, Woodward, Mark, Ahmadvand, Alireza, Aguilar-Salinas, Carlos A, Azizi, Fereidoun, Cifkova, Renata +20 more·2015·The Lancet Diabetes & Endocrinology

Abstract

Background Treatment of cardiovascular risk factors based on disease risk depends on valid risk prediction equations. We aimed to develop, and apply in example countries, a risk prediction equation for cardiovascular disease (consisting here of coronary heart disease and stroke) that can be recalibrated and updated for application in different countries with routinely available information.Methods We used data from eight prospective cohort studies to estimate coefficients of the risk equation with proportional hazard regressions. The risk prediction equation included smoking, blood pressure, diabetes, and total cholesterol, and allowed the effects of sex and age on cardiovascular disease to vary between cohorts or countries. We developed risk equations for fatal cardiovascular disease and for fatal plus non-fatal cardiovascular disease. We validated the risk equations internally and also using data from three cohorts that were not used to create the equations. We then used the risk prediction equation and data from recent (2006 or later) national health surveys to estimate the proportion of the population at different levels of cardiovascular disease risk in 11 countries from different world regions (China, Czech Republic, Denmark, England, Iran, Japan, Malawi, Mexico, South Korea, Spain, and USA).Findings The risk score discriminated well in internal and external validations, with C statistics generally 70% or more. At any age and risk factor level, the estimated 10 year fatal cardiovascular disease risk varied substantially between countries. The prevalence of people at high risk of fatal cardiovascular disease was lowest in South Korea, Spain, and Denmark, where only 5-10% of men and women had more than a 10% risk, and 62-77% of men and 79-82% of women had less than a 3% risk. Conversely, the proportion of people at high risk of fatal cardiovascular disease was largest in China and Mexico. In China, 33% of men and 28% of women had a 10-year risk of fatal cardiovascular disease of 10% or more, whereas in Mexico, the prevalence of this high risk was 16% for men and 11% for women. The prevalence of less than a 3% risk was 37% for men and 42% for women in China, and 55% for men and 69% for women in Mexico.Interpretation We developed a cardiovascular disease risk equation that can be recalibrated for application in different countries with routinely available information. The estimated percentage of people at high risk of fatal cardiovascular disease was higher in low-income and middle-income countries than in high-income countries.Funding US National Institutes of Health, UK Medical Research Council, Wellcome Trust.

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  • Most guidelines adopt one of the available risk assessment systems.

    “Most guidelines use one of these risk assessment systems [6-8].”
  • 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 [50]

  • Most guidelines use one of the available risk estimation systems.

    “Most guidelines use one of these risk estimation systems. 50-52”

    From 2016 ESC/EAS Guidelines for the Management of Dyslipidaemias (2016) · cites this paper as [50]

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References 51 · Cited by 287

Research works printed but not linked: 1

  1. [44]Matheny M McPheeters ML Glasser A Mercaldo N Weaver RB Jerome RN Systematic Review of Cardiovascular Disease Risk Assessment Tools Rockville (MD) 2011 21796824

Authors
Hajifathalian, K., Ueda, P., Lu, Y., Woodward, M., Ahmadvand, A., Aguilar-Salinas, C. A., Azizi, F., Cifkova, R., Di Cesare, M., Eriksen, L., Farzadfar, F., Ikeda, N., Khalili, D., Khang, Y.-H., Lanska, V., León-Muñoz, L., Magliano, D., Msyamboza, K. P., Oh, K., Rodríguez-Artalejo, F., Rojas-Martinez, R., Shaw, J. E., Stevens, G. A., Tolstrup, J., Zhou, B., Salomon, J. A., Ezzati, M., & Danaei, G.
Affiliations
  • Cleveland Clinic (US)
  • Harvard University (US)
  • The University of Sydney (AU)
  • MRC Centre for Environment and Health (GB)
  • Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán (MX)
  • Research Institute for Endocrine Sciences (IR)
  • University of Southern Denmark (DK)
  • Endocrinology and Metabolism Population Sciences Institute (IR)
  • National Institute of Health and Nutrition (JP)
  • Seoul National University (KR)
  • Centro de Investigación Biomédica en Red (ES)
  • Baker Heart and Diabetes Institute (AU)
  • World Health Organization - Malawi (MW)
  • Korea Disease Control and Prevention Agency (KR)
  • World Health Organization (CH)
  • Thomayer University Hospital (CZ)
Corresponding author
Danaei, Goodarz
Venue
The Lancet Diabetes & Endocrinology
Publisher
Elsevier BV
Published
2015-05
Volume
3
Issue
5
Pages
339-355
ISSN
2213-8587 (ISSN-L)
OpenAlex
W2094918523
Cited by
287
References
51
Citations by year
2026: 20 · 2025: 28 · 2024: 41 · 2023: 29 · 2022: 24 · 2021: 28 · 2020: 30 · 2019: 21 · 2018: 21 · 2017: 14 · 2016: 23 · 2015: 8
FWCI
16.01
Type
journal article
Language
en
Open access
Locations
  • The Lancet Diabetes & Endocrinology (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • Middlesex University Research Repository (Middlesex University Of London) (submittedVersion)
  • Seoul National University Open Repository (Seoul National University) (submittedVersion)
  • University of Southern Denmark Research Portal (University of Southern Denmark) (submittedVersion)
  • Spiral (Imperial College London) (submittedVersion, cc-by-nc-nd)
Funders
  • US National Institutes of Health (1R01-DK090435)
  • Grant-in-Aid for Scientific Research from the Japan Society for the Promotion of Science (grant number: 24590785)
Topics
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Health and Risk Factors
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Health Promotion and Cardiovascular Prevention
  • Health Sciences › Medicine › Surgery › Lipoproteins and Cardiovascular Health
Keywords
cardiovascular risk prediction, Globorisk, risk score, coronary artery disease, stroke, pooled analysis, risk recalibration, smoking, blood pressure, diabetes mellitus, total cholesterol, 10-year risk, cross-national comparison, low-income countries, sex differences, health examination surveys, prospective cohort, China, Mexico, South Korea, Denmark, Spain, Japan
MeSH terms
Adult, Aged, Calibration, Cardiovascular Diseases, Coronary Disease, Diagnostic Techniques, Cardiovascular, Female, Health Status Indicators, Humans, Male, Middle Aged, Prospective Studies, Risk Factors, Proportional Hazards Models, Risk Assessment, Stroke

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