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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
Open accessAbstract
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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“There are several assessment tool that predict the absolute risk of ASCVD in the Japanese population.”
From Japan Atherosclerosis Society (JAS) guidelines for prevention of atherosclerotic cardiovascular diseases 2017 (2018) · cites this paper as [161]
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“In terms of absolute risk, aging enhances the risk for ASCVD and death from it much more than any other risk factors160–162).”
From Japan Atherosclerosis Society (JAS) guidelines for prevention of atherosclerotic cardiovascular diseases 2017 (2018) · cites this paper as [161]
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Kinoshita, M., Yokote, K., Arai, H., Iida, M., Ishigaki, Y., Ishibashi, S., Umemoto, S., Egusa, G., Ohmura, H., Okamura, T., et al. (2018) · Journal of Atherosclerosis and Thrombosis · doi:10.5551/jat.gl2017 · Cited by 813
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Self-citationAn international multidisciplinary consensus statement on MAFLD and the risk of CVD
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“Several studies from different countries showed that patients with MAFLD had a higher 10-year CVD risk (as estimated by the FRS or other CVD risk prediction tools) compared to those with NAFLD, thus confirming that MAFLD may identify a greater CVD risk burden [25, 27, 38, 39].”
BackgroundResultBiomarkers of Cardiovascular Disease and Mortality Risk in Patients with Advanced CKD
Sun, J. T., Axelsson, J., Machowska, A., Heimbürger, O., Barany, P. F., Lindholm, B., Lindström, K., Stenvinkel, P., & Qureshi, A. R. (2016) · Clinical Journal of the American Society of Nephrology · doi:10.2215/cjn.10441015 · Cited by 183
“Over the last decade, multiple studies have attempted to identify better risk prediction tools specific to the CKD population (7,12,13).”
BackgroundTsutsumi, T., Eslam, M., Kawaguchi, T., Yamamura, S., Kawaguchi, A., Nakano, D., Koseki, M., Yoshinaga, S., Takahashi, H., Anzai, K., et al. (2021) · Hepatology Research · doi:10.1111/hepr.13685 · Cited by 170
“On the other hand, MAFLD was an independent factor for worsening of the Suita score that has been developed for Japanese patients.(8) Thus, MAFLD was an independent predictor only for worsening of Suita score, not for the Framingham risk score.”
BackgroundMethodInfluential
Metadata
- 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)
- ORCID
- Venue
- Journal of Atherosclerosis and Thrombosis
- Publisher
- Japan Atherosclerosis Society
- Published
- 2014
- Volume
- 21
- Issue
- 8
- Pages
- 784-798
- ISSN
- 1340-3478 (ISSN-L)
- 1880-3873
- PMC
- PMC5090819
- 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
- hybrid
- doi.org
- 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 › Cardiology and Cardiovascular Medicine › 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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