动脉样硬化心血管疾病的风险预测,有或没有种族分层
Arnab K Ghosh1, Sara Venkatraman1,2, Michael G Nanna3
1Department of Medicine, Weill Cornell Medical College, Cornell University, New York, New York.
JAMA cardiology
|December 6, 2023
概括
动脉样硬化心血管疾病 (ASCVD) 风险预测的聚合队列方程 (PCE) 显示了具有或没有种族分层的类似表现. 在REGARDS研究中,添加健康的社会决定因素 (SDOH) 并没有提高模型的准确性.
科学领域:
- 心血管疾病流行病学
- 风险预测建模风险预测建模
- 健康差异研究 研究健康差异研究
背景情况:
- 种族特异性风险预测工具,如动脉样硬化心血管疾病 (ASCVD) 的聚合队列方程 (PCE),在临床医学中越来越受到质疑.
- 目前的ASCVD风险评估标准依赖于种族分层,促使人们对其必要性和替代预测因素的潜力进行调查.
研究的目的:
- 评估种族特异性PCE在ASCVD风险预测中的附加值.
- 确定是否结合健康的社会决定因素 (SDOH) 与基于种族的分层相比,可以提高模型的性能.
主要方法:
- 对脑卒中地理和种族差异双种族原因的分析 (REGARDS) 前性队列研究 (n=11,638).
- 在45-79岁的参与者中,没有ASCVD,并且具有特定胆固醇水平,在10年内对发生的ASCVD进行了跟踪.
- 模型的性能被评估使用歧视 (C统计,净重新分类指数) 和校准 (Nam D'Agostino测试) 原始PCE,种族分层模型,没有种族的模型和包括SDOH的模型.
主要成果:
- 总体而言,PCE的表现良好,但与所有模型中的女性参与者相比,黑人男性 (BM) 和白人男性 (WM) 参与者表现较差.
- 与种族分层模型 (模型C) 相比,消除种族分层 (模型D) 或添加SDOH (模型E) 的歧视 (C统计) 并没有实质性变化.
- 净重新分类指数显示,当SDOH取代种族时,男性的高风险正确分配略有下降,但女性没有. 在所有子组和模型中,校准仍然很好.
结论:
- 对于ASCVD风险预测,PCE中的种族分层提供了最小的增量价值.
- 用SDOH取代种族并没有提高研究队列中的模型性能.
- 可能需要进一步的研究来完善风险预测模型,可能专注于超越种族和当前SDOH措施的因素.
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