心血管风险预测中的性别不平等
Joshua Elliott1,2,3,4, Barbara Bodinier3,5, Matthew Whitaker3,5
1Department of Infectious Diseases, Faculty of Medicine, Imperial College London, London, UK.
Cardiovascular research
|June 4, 2024
概括
心血管疾病风险预测模型在目前的值下,女性的表现比男性差. 调整风险值,特别是使用女性5%的十年风险,可以显著提高预测准确度.
科学领域:
- 心脏病学 心脏病学
- 流行病学 流行病学
- 生物统计学 生物统计学
背景情况:
- 心血管疾病 (CVD) 风险预测对于预防策略至关重要.
- 现有的风险计算器可能会显示基于性别的绩效差异.
- 最佳的性别特异性预测指标和值需要进一步调查.
研究的目的:
- 评估心血管疾病 (CVD) 风险预测中的性别差异.
- 评估性别特定风险预测指标和值的有用性.
- 为了比较男性和女性不同心血管疾病风险模型的表现.
主要方法:
- 使用英国生物库数据进行的前性队列研究 (121,724名男性,182,632名女性).
- 事件心血管疾病病例 (住院/死亡) 被追踪了平均12.1年.
- 通过LASSO选择的性别特定变量对比聚合队列方程 (PCE),QRISK3和Cox模型.
主要成果:
- 在各种模型中,C-统计数据在性别之间是相似的 (PCE,QRISK3,LASSO选择的变量).
- 在当前风险值 (例如,7.5%和10%) 的情况下,女性的模型灵敏度明显低于男性.
- 在目前的值下,女性的特异性比男性高.
- 妇女的敏感性在5%的10年风险值下大大改善.
结论:
- 稀少的性别特异变量改善了心血管疾病风险预测比PCE,但不是QRISK3.
- 目前对PCE和QRISK3的风险值对女性来说不那么有效.
- 建议重新评估心血管疾病风险计算器,以纳入性别特定的门值.
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