Sex inequalities in cardiovascular risk prediction.

IF 10.2 1区 医学 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS Cardiovascular Research Pub Date : 2024-09-21 DOI:10.1093/cvr/cvae123
Joshua Elliott, Barbara Bodinier, Matthew Whitaker, Rin Wada, Graham Cooke, Helen Ward, Ioanna Tzoulaki, Paul Elliott, Marc Chadeau-Hyam
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引用次数: 0

Abstract

Aims: Evaluate sex differences in cardiovascular disease (CVD) risk prediction, including use of (i) optimal sex-specific risk predictors and (ii) sex-specific risk thresholds.

Methods and results: Prospective cohort study using UK Biobank, including 121 724 and 182 632 healthy men and women, respectively, aged 38-73 years at baseline. There were 11 899 (men) and 9110 (women) incident CVD cases (hospitalization or mortality) with a median of 12.1 years of follow-up. We used recalibrated pooled cohort equations (PCEs; 7.5% 10-year risk threshold as per US guidelines), QRISK3 (10% 10-year risk threshold as per UK guidelines), and Cox survival models using sparse sex-specific variable sets (via LASSO stability selection) to predict CVD risk separately in men and women. LASSO stability selection included 12 variables in common between men and women, with 3 additional variables selected for men and 1 for women. C-statistics were slightly lower for PCE than QRISK3 and models using stably selected variables, but were similar between men and women: 0.67 (0.66-0.68), 0.70 (0.69-0.71), and 0.71 (0.70-0.72) in men and 0.69 (0.68-0.70), 0.72 (0.71-0.73), and 0.72 (0.71-0.73) in women for PCE, QRISK3, and models using stably selected variables, respectively. At current clinically implemented risk thresholds, test sensitivity was markedly lower in women than men for all models: at 7.5% 10-year risk, sensitivity was 65.1 and 68.2% in men and 24.0 and 33.4% in women for PCE and models using stably selected variables, respectively; at 10% 10-year risk, sensitivity was 53.7 and 52.3% in men and 16.8 and 20.2% in women for QRISK3 and models using stably selected variables, respectively. Specificity was correspondingly higher in women than men. However, the sensitivity in women at 5% 10-year risk threshold increased to 50.1, 58.5, and 55.7% for PCE, QRISK3, and models using stably selected variables, respectively.

Conclusion: Use of sparse sex-specific variables improved CVD risk prediction compared with PCE but not QRISK3. At current risk thresholds, PCE and QRISK3 work less well for women than men, but sensitivity was improved in women using a 5% 10-year risk threshold. Use of sex-specific risk thresholds should be considered in any re-evaluation of CVD risk calculators.

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心血管风险预测中的性别不平等。
目的:评估心血管疾病(CVD)风险预测中的性别差异,包括使用 i)最佳性别特异性风险预测因子和 ii)性别特异性风险阈值:利用英国生物数据库进行前瞻性队列研究,研究对象包括基线年龄在 38-73 岁之间的健康男性和女性,分别为 121,724 人和 182,632 人。在中位 12.1 年的随访中,分别有 11,899 例(男性)和 9,110 例(女性)心血管疾病病例(住院或死亡)。我们使用重新校准的集合队列方程(PCE,根据美国指南,10 年风险阈值为 7.5%)、QRISK3(根据英国指南,10 年风险阈值为 10%)和 Cox 生存模型,使用稀疏的性别特异性变量集(通过 LASSO 稳定性选择)分别预测男性和女性的心血管疾病风险。LASSO 稳定性选择包括男女共同的 12 个变量,另外还为男性选择了三个变量,为女性选择了一个变量。PCE的C统计量略低于QRISK3和使用稳定选择变量的模型,但男女之间的C统计量相似:PCE、QRISK3和使用稳定选择变量的模型的男性C统计量分别为0.67 [0.66-0.68]、0.70 [0.69-0.71]和0.71 [0.70-0.72],女性C统计量分别为0.69 [0.68-0.70]、0.72 [0.71-0.73]和0.72 [0.71-0.73]。在目前临床应用的风险阈值下,女性对所有模型的检测灵敏度都明显低于男性:10 年风险为 7.5% 时,男性对 PCE 和使用稳定选择变量模型的灵敏度分别为 65.1% 和 68.2%,女性为 24.0% 和 33.4%;10 年风险为 10% 时,男性对 QRISK3 和使用稳定选择变量模型的灵敏度分别为 53.7% 和 52.3%,女性为 16.8% 和 20.2%。女性的特异性也相应高于男性。然而,在5%的10年风险阈值下,PCE、QRISK3和使用稳定选择变量的模型对女性的灵敏度分别增加到50.1%、58.5%和55.7%:与 PCE 相比,使用稀疏的性别特异性变量可提高心血管疾病风险预测能力,但 QRISK3 则不然。在目前的风险阈值下,PCE 和 QRISK3 对女性的预测效果不如男性,但在使用 5% 10 年风险阈值时,女性的灵敏度有所提高。在对心血管疾病风险计算器进行任何重新评估时,都应考虑使用特定性别的风险阈值:心血管疾病(CVD)风险预测是临床风险管理和疾病预防的重要组成部分。我们发现,在目前应用的风险预测算法所使用的风险预测阈值(美国的 PCE 7.5% 10 年风险阈值和英国的 QRISK3 10% 风险阈值)下,女性对这些风险预测工具的敏感性明显低于男性。这种性别不平等意味着女性接受包括降脂治疗在内的适当临床管理的可能性更小。如果将女性的风险预测阈值降低到 10 年风险的 5%,那么女性的敏感性就会大大提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Cardiovascular Research
Cardiovascular Research 医学-心血管系统
CiteScore
21.50
自引率
3.70%
发文量
547
审稿时长
1 months
期刊介绍: Cardiovascular Research Journal Overview: International journal of the European Society of Cardiology Focuses on basic and translational research in cardiology and cardiovascular biology Aims to enhance insight into cardiovascular disease mechanisms and innovation prospects Submission Criteria: Welcomes papers covering molecular, sub-cellular, cellular, organ, and organism levels Accepts clinical proof-of-concept and translational studies Manuscripts expected to provide significant contribution to cardiovascular biology and diseases
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