利用日本城市人群的危险因素类别预测冠心病，并与弗雷明汉风险评分进行比较：吹田研究
Predicting coronary heart disease using risk factor categories for a Japanese urban population, and comparison with the framingham risk score: the suita study.
作者信息
Nishimura Kunihiro, Okamura Tomonori, Watanabe Makoto, Nakai Michikazu, Takegami Misa, Higashiyama Aya, Kokubo Yoshihiro, Okayama Akira, Miyamoto Yoshihiro
机构信息
Department of Preventive Medicine, National Cerebral and Cardiovascular Center.
出版信息
J Atheroscler Thromb. 2014;21(8):784-98. doi: 10.5551/jat.19356. Epub 2014 Mar 25.
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.
目的
弗雷明汉风险评分（FRS）是用于预测冠心病（CHD）发病率的标准工具之一。此前尚无研究调查其在日本人群队列中的有效性。本研究的目的是以FRS的方式为日本人群开发新的冠心病预测算法，并将其与原始FRS进行比较。
方法
我们针对日本人的冠心病预测算法基于一项大型的基于人群的队列研究（吹田研究）。研究人群包括5521名健康的日本人。他们平均随访了11.8年，观察到213例冠心病病例。采用逐步选择的多因素Cox比例风险模型构建预测模型。
结果
我们针对日本患者的冠心病预测算法基于一项大型的基于人群的队列研究（吹田研究）。采用逐步选择的多因素Cox比例风险模型构建预测模型。C统计量表明，新模型比原始和重新校准的弗雷明汉评分具有更高的准确性。与原始FRS相比，纳入慢性肾脏病（CKD）的吹田评分的净重新分类改善（NRI）为41.2%（P＜0.001）。FRS的重新校准略微提高了预测效率，但仍比包含CKD模型的吹田评分差。校准分析表明，原始FRS和重新校准的FRS高估了日本人群中冠心病的风险。包含CKD的吹田评分更准确地预测了冠心病风险。
结论
FRS和重新校准的FRS高估了日本人群冠心病的10年风险。就C统计量和NRI而言，将CKD作为冠心病风险因素纳入的预测评分在预测日本人群冠心病方面比原始弗雷明汉风险评分更准确。
Zotero 插件