中国北方农村人群动脉粥样硬化性心血管病风险预测模型的表现:来自房山队列研究的结果。
Performance of atherosclerotic cardiovascular risk prediction models in a rural Northern Chinese population: Results from the Fangshan Cohort Study.
机构信息
Department of Epidemiology and Biostatistics, Peking University Health Science Center, Beijing, China.
Fangshan District Center for Disease Control and Prevention, Beijing, China.
出版信息
Am Heart J. 2019 May;211:34-44. doi: 10.1016/j.ahj.2019.01.009. Epub 2019 Feb 5.
BACKGROUND
Performance of Pooled Cohort Equations (PCEs) for atherosclerotic cardiovascular disease (ASCVD) risks varied across populations. Whether the recently developed Prediction for ASCVD Risk in China (China-PAR) model could accurately predict cardiovascular risks in real practice remains unclear.
METHODS
A population-based cohort study in rural Beijing in the "stroke belt" in North China was used to externally validate PCE and China-PAR models for 5-year ASCVD risk prediction. Expected 5-year prediction risk using China-PAR model was compared with PCE (white). The models were assessed for calibration, discrimination, and reclassification.
RESULTS
Among 11,169 adults aged 40 to 79 years over a median 6.44 years of follow-up, 1,921 participants developed a first ASCVD event during total 70,951 person-years. China-PAR model fairly predicted ASCVD risk in men but overestimated by 29.4% risk in women (calibration χ = 81.4, P < .001). Underestimations were shown by PCE as 76.2% in men and 88.2% in women with poor calibration (both P < .001). However, discrimination was similar in both models: C-statistics in men were 0.685 (95% CI 0.660-0.710) for China-PAR and 0.675 (95% CI 0.649-0.701) for PCE; C-statistics in women were 0.711 (95% CI 0.694-0.728) for China-PAR and 0.714 (95% CI 0.697-0.731) for PCE. Moreover, China-PAR did not substantially improve accuracy of reclassification compared with PCE.
CONCLUSIONS
China-PAR outperformed PCE in 5-year ASCVD risk prediction in this rural Northern Chinese population at average population risk level, fairly predicted risk in men, but overestimated risk in women; however, China-PAR did not meaningfully improve the accuracy of discrimination and reclassification at individual risk level.
背景
用于动脉粥样硬化性心血管疾病(ASCVD)风险的汇总队列方程(PCE)在不同人群中的表现存在差异。最近开发的用于中国 ASCVD 风险预测的预测模型(China-PAR)是否能在实际实践中准确预测心血管风险尚不清楚。
方法
本研究采用基于人群的队列研究,在北京北部农村的“中风带”进行,用于验证 PCE 和 China-PAR 模型在预测 5 年 ASCVD 风险方面的外部有效性。使用 China-PAR 模型预测的预期 5 年风险与 PCE(白色)进行比较。评估了模型的校准、区分和重新分类能力。
结果
在中位随访 6.44 年期间,共有 11169 名年龄在 40 至 79 岁的成年人,在总计 70951 人年中,有 1921 人发生了首次 ASCVD 事件。China-PAR 模型在男性中较好地预测了 ASCVD 风险,但在女性中高估了 29.4%的风险(校准 χ2=81.4,P<0.001)。PCE 则低估了男性的风险 76.2%,低估了女性的风险 88.2%,校准效果较差(均 P<0.001)。然而,两个模型的区分度相似:男性的 C 统计量分别为 China-PAR 0.685(95%置信区间 0.660-0.710)和 PCE 0.675(95%置信区间 0.649-0.711);女性的 C 统计量分别为 China-PAR 0.711(95%置信区间 0.694-0.728)和 PCE 0.714(95%置信区间 0.697-0.731)。此外,China-PAR 在个体风险水平上并没有显著提高重新分类的准确性。
结论
在平均人群风险水平上,China-PAR 在预测该北方农村人群的 5 年 ASCVD 风险方面优于 PCE,在男性中风险预测较好,但在女性中高估了风险;然而,China-PAR 在个体风险水平上并没有显著提高区分度和重新分类的准确性。