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日本成年人动脉粥样硬化性心血管疾病风险预测模型的建立与验证:日上山研究。

Development and Validation of a Risk Prediction Model for Atherosclerotic Cardiovascular Disease in Japanese Adults: The Hisayama Study.

机构信息

Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University.

Center for Cohort Studies, Graduate School of Medical Sciences, Kyushu University.

出版信息

J Atheroscler Thromb. 2022 Mar 1;29(3):345-361. doi: 10.5551/jat.61960. Epub 2021 Jan 22.

Abstract

AIM

To develop and validate a new risk prediction model for predicting the 10-year risk of atherosclerotic cardiovascular disease (ASCVD) in Japanese adults.

METHODS

A total of 2,454 participants aged 40-84 years without a history of cardiovascular disease (CVD) were prospectively followed up for 24 years. An incident ASCVD event was defined as the first occurrence of coronary heart disease or atherothrombotic brain infarction. A Cox proportional hazards regression model was used to construct the prediction model. In addition, a simplified scoring system was translated from the developed prediction model. The model performance was evaluated using Harrell's C statistics, a calibration plot with the Greenwood-Nam-D'Agostino test, and a bootstrap validation procedure.

RESULTS

During a median of a 24-year follow-up, 270 participants experienced the first ASCVD event. The predictors of the ASCVD events in the multivariable Cox model included age, sex, systolic blood pressure, diabetes, serum high-density lipoprotein cholesterol, serum low-density lipoprotein cholesterol, proteinuria, smoking habits, and regular exercise. The developed models exhibited good discrimination with negligible evidence of overfitting (Harrell's C statistics: 0.786 for the multivariable model and 0.789 for the simplified score) and good calibrations (the Greenwood-Nam-D'Agostino test: P=0.29 for the multivariable model, 0.52 for the simplified score).

CONCLUSION

We constructed a risk prediction model for the development of ASCVD in Japanese adults. This prediction model exhibits great potential as a tool for predicting the risk of ASCVD in clinical practice by enabling the identification of specific risk factors for ASCVD in individual patients.

摘要

目的

开发和验证一种新的风险预测模型,以预测日本成年人发生动脉粥样硬化性心血管疾病(ASCVD)的 10 年风险。

方法

共前瞻性随访了 2454 名年龄在 40-84 岁、无心血管疾病(CVD)病史的参与者,随访时间为 24 年。ASCVD 事件的定义为首次发生冠心病或动脉粥样血栓性脑梗死。采用 Cox 比例风险回归模型构建预测模型。此外,还从开发的预测模型中翻译了一个简化的评分系统。采用 Harrell 的 C 统计量、Greenwood-Nam-D'Agostino 检验的校准图和 bootstrap 验证程序评估模型性能。

结果

在中位数为 24 年的随访期间,270 名参与者发生了首次 ASCVD 事件。多变量 Cox 模型中 ASCVD 事件的预测因素包括年龄、性别、收缩压、糖尿病、血清高密度脂蛋白胆固醇、血清低密度脂蛋白胆固醇、蛋白尿、吸烟习惯和规律运动。开发的模型具有良好的区分度,几乎没有过度拟合的证据(Harrell 的 C 统计量:多变量模型为 0.786,简化评分模型为 0.789),且校准良好(Greenwood-Nam-D'Agostino 检验:多变量模型为 0.29,简化评分模型为 0.52)。

结论

我们构建了一个日本成年人 ASCVD 发病风险的预测模型。该预测模型通过识别个体患者 ASCVD 的特定风险因素,有望成为临床实践中预测 ASCVD 风险的工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/52d9/8894117/95419c7993d6/29_61960_1.jpg

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