Prediction of Coronary Artery Disease and Major Adverse Cardiovascular Events Using Clinical and Genetic Risk Scores for Cardiovascular Risk Factors

被引:8
作者
Ramirez, Julia [1 ,2 ]
van Duijvenboden, Stefan [1 ,3 ]
Young, William J. [1 ,4 ]
Tinker, Andrew [1 ,5 ]
Lambiase, Pier D. [3 ,4 ]
Orini, Michele [3 ,4 ]
Munroe, Patricia B. [1 ,5 ]
机构
[1] Queen Mary Univ London, Barts & London Sch Med & Dent, William Harvey Res Inst, Clin Pharmacol & Precis Med Deparment, Charterhouse Sq, London EC1M 6BQ, England
[2] Univ Zaragoza, Aragon Inst Engn Res, Elect Engn & Commun Dept, Zaragoza, Spain
[3] UCL, Inst Cardiovasc Sci, London, England
[4] St Bartholomews Hosp, Barts Heart Ctr, London, England
[5] Queen Mary Univ London, NIHR Barts Cardiovasc Biomed Res Ctr, Barts & London Sch Med & Dent, London, England
基金
欧盟地平线“2020”; 英国医学研究理事会;
关键词
coronary artery disease; epidemiology; genetic predisposition; genetic screening; risk factors; QT INTERVAL DURATION; ASSOCIATION; LOCI; PREVENTION; MORTALITY; VARIANTS; ACCURACY; THERAPY;
D O I
10.1161/CIRCGEN.121.003441
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background: Coronary artery disease (CAD) and major adverse cardiovascular events (MACE) are the leading causes of death in the general population, but risk stratification remains suboptimal. CAD genetic risk scores (GRSs) predict risk independently from clinical tools, like QRISK3. We assessed the added value of GRSs for a variety of cardiovascular traits (CV GRSs) for predicting CAD and MACE and tested their early-life screening potential by comparing against the CAD GRS only. Methods: We used data from 379 581 participants in the UK Biobank without known cardiovascular conditions (follow-up, 11.3 years; 3.3% CAD cases and 5.2% MACE cases). In a training subset (50%) we built 3 scores: QRISK3; QRISK3 and an established CAD GRS; and QRISK3, the CAD GRS and the CV GRSs. In an independent subset (50%), we evaluated each score's performance using the concordance index, odds ratio and net reclassification index. We then repeated the analyses without considering QRISK3. Results: For CAD, the combination of QRISK3 and the CAD GRS had a better performance than QRISK3 alone (concordance index, 0.766 versus 0.753; odds ratio, 5.47 versus 4.82; net reclassification index, 7.7%). Adding the CV GRSs did not significantly improve risk stratification. When only looking at genetic information, the combination of CV GRSs and the CAD GRS had a better performance than the CAD GRS alone (concordance index, 0.637 versus 0.625; odds ratio, 2.17 versus 2.07; net reclassification index, 3.3%). Similar results were obtained for MACE. Conclusions: In individuals without known cardiovascular disease, the inclusion of CV GRSs to a clinical tool and an established CAD GRS does not improve CAD or MACE risk stratification. However, their combination only with the CAD GRS increases prediction performance indicating potential use in early-life screening before the advanced development of conventional cardiovascular risk factors.
引用
收藏
页码:444 / 452
页数:9
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