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Predicting Coronary Heart Disease Using Risk Factor Categories for a Japanese Urban Population, and Comparison with the Framingham Risk Score: The Suita Study

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Nishimura, Kunihiro, Okamura, Tomonori, Watanabe, Makoto, Nakai, Michikazu, Takegami, Misa, Higashiyama, Aya, Kokubo, Yoshihiro, Okayama, Akira +1 more·2014·Journal of Atherosclerosis and Thrombosis

Abstract

AIM: The Framingham risk score (FRS) is one of the standard tools used to predict the incidence of coronary heart disease (CHD). No previous study has investigated its efficacy for a Japanese population cohort. The purpose of this study was to develop new coronary prediction algorithms for the Japanese population in the manner of the FRS, and to compare them with the original FRS. METHODS: Our coronary prediction algorithms for Japanese were based on a large population-based cohort study (Suita study). The study population comprised 5,521 healthy Japanese. They were followed-up for 11.8 years on average, and 213 cases of CHD were observed. Multiple Cox proportional hazard model by stepwise selection was used to construct the prediction model. RESULTS: Our coronary prediction algorithms for Japanese patients were based on a large populationbased cohort study (the Suita study). A multiple Cox proportional hazard model by stepwise selection was used to construct the prediction model. The C-statistics showed that the new model had better accuracy than the original and recalibrated Framingham scores. The net reclassification improvement (NRI) by the Suita score with the inclusion of CKD was 41.2% (P<0.001) compared with the original FRS. The recalibration of the FRS slightly improved the efficiency of the prediction, but it was still worse than the Suita score with the CKD model. The calibration analysis suggested that the original FRS and the recalibrated FRS overestimated the risk of CHD in the Japanese population. The Suita score with CKD more accurately predicted the risk of CHD. CONCLUSION: The FRS and recalibrated FRS overestimated the 10-year risk of CHD for the Japanese population. A predictive score including CKD as a coronary risk factor for the Japanese population was more accurate for predicting CHD than the original Framingham risk scores in terms of the C-statics and NRI.

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  1. MacMahon S, Peto R, Cutler J, Collins R, Sorlie P, Nea- ton J, Abbott R, Godwin J, Dyer A, Stamler J: Blood pressure, stroke, and coronary heart disease. Part 1, pro- longed differences in blood pressure: Prospective observa- cohort study in japan, the suita study. Int J Epidemiol, 2009; 38: 1571-1579

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Authors
Nishimura, K., Okamura, T., Watanabe, M., Nakai, M., Takegami, M., Higashiyama, A., Kokubo, Y., Okayama, A., & Miyamoto, Y.
Affiliations
  • National Cerebral and Cardiovascular Center (JP)
  • Keio University (JP)
  • Hyogo Medical University (JP)
  • Japan Anti Tuberculosis Association (JP)
Venue
Journal of Atherosclerosis and Thrombosis
Published
2014
Volume
21
Issue
8
Pages
784-798
ISSN
  • 1340-3478 (ISSN-L)
  • 1880-3873
OpenAlex
W2043022783
Cited by
228
References
58
Citations by year
2026: 10 · 2025: 13 · 2024: 25 · 2023: 25 · 2022: 34 · 2021: 33 · 2020: 20 · 2019: 19 · 2018: 20 · 2017: 10 · 2016: 12 · 2015: 4 · 2014: 2
FWCI
9.29
Type
journal article
Language
en
Open access
Licence
cc-by-nc-sa
Locations
  • Journal of Atherosclerosis and Thrombosis (publishedVersion, cc-by-nc-sa)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
  • National Cerebral and Cardiovascular Center (22-4-5)
  • Japan Society for the Promotion of Science (25293147)
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
coronary artery disease, Framingham risk score, risk prediction model, Japanese population, chronic kidney disease, Suita Study, risk overestimation, net reclassification improvement, 10-year risk, urban population
MeSH terms
Adult, Aged, Algorithms, Coronary Disease, Female, Follow-Up Studies, Humans, Japan, Male, Middle Aged, Prognosis, Risk Factors, Urban Population, Cohort Studies, Biomarkers, Incidence, Proportional Hazards Models, Case-Control Studies, Risk Assessment

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