Predicting coronary heart disease using risk factor categories for a Japanese urban population, and comparison with the Framingham risk score: The Suita study

Kunihiro Nishimura, Tomonori Okamura, Makoto Watanabe, Michikazu Nakai, Misa Takegami, Aya Higashiyama, Yoshihiro Kokubo, Akira Okayama, Yoshihiro Miyamoto

研究成果: Article

44 引用 (Scopus)

抄録

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 population-based 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.

元の言語English
ページ(範囲)784-798
ページ数15
ジャーナルJournal of Atherosclerosis and Thrombosis
21
発行部数8
DOI
出版物ステータスPublished - 2014

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Urban Population
Coronary Disease
Population
Proportional Hazards Models
Cohort Studies
Hazards
Calibration

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine
  • Internal Medicine
  • Biochemistry, medical
  • Medicine(all)

これを引用

Predicting coronary heart disease using risk factor categories for a Japanese urban population, and comparison with the Framingham risk score : The Suita study. / Nishimura, Kunihiro; Okamura, Tomonori; Watanabe, Makoto; Nakai, Michikazu; Takegami, Misa; Higashiyama, Aya; Kokubo, Yoshihiro; Okayama, Akira; Miyamoto, Yoshihiro.

:: Journal of Atherosclerosis and Thrombosis, 巻 21, 番号 8, 2014, p. 784-798.

研究成果: Article

Nishimura, Kunihiro ; Okamura, Tomonori ; Watanabe, Makoto ; Nakai, Michikazu ; Takegami, Misa ; Higashiyama, Aya ; Kokubo, Yoshihiro ; Okayama, Akira ; Miyamoto, Yoshihiro. / Predicting coronary heart disease using risk factor categories for a Japanese urban population, and comparison with the Framingham risk score : The Suita study. :: Journal of Atherosclerosis and Thrombosis. 2014 ; 巻 21, 番号 8. pp. 784-798.
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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 population-based 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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author = "Kunihiro Nishimura and Tomonori Okamura and Makoto Watanabe and Michikazu Nakai and Misa Takegami and Aya Higashiyama and Yoshihiro Kokubo and Akira Okayama and Yoshihiro Miyamoto",
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TY - JOUR

T1 - Predicting coronary heart disease using risk factor categories for a Japanese urban population, and comparison with the Framingham risk score

T2 - The Suita study

AU - Nishimura, Kunihiro

AU - Okamura, Tomonori

AU - Watanabe, Makoto

AU - Nakai, Michikazu

AU - Takegami, Misa

AU - Higashiyama, Aya

AU - Kokubo, Yoshihiro

AU - Okayama, Akira

AU - Miyamoto, Yoshihiro

PY - 2014

Y1 - 2014

N2 - 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 population-based 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.

AB - 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 population-based 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.

KW - Coronary heart disease

KW - Framingham risk score

KW - Japanese cohort

KW - Risk score

KW - Suita study

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