Imperial College London
Alternate

Prof Marc Chadeau-Hyam

Faculty of Medicine, School of Public Health

Professor of Computational Epidemiology and Biostatistics
 
 
 
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Contact

 

+44 (0)20 7594 1637m.chadeau

 
 
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Location

 

520Medical SchoolSt Mary's Campus

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Summary

 

Publications

Citation

BibTex format

@article{Elliott:2020:10.1001/jama.2019.22241,
author = {Elliott, J and Bodinier, B and Bond, TA and Chadeau-Hyam, M and Evangelou, E and Moons, KGM and Dehghan, A and Muller, DC and Elliott, P and Tzoulaki, I},
doi = {10.1001/jama.2019.22241},
journal = {JAMA: Journal of the American Medical Association},
pages = {636--645},
title = {Predictive accuracy of a polygenic risk score-enhanced prediction model vs a clinical risk score for coronary artery disease},
url = {http://dx.doi.org/10.1001/jama.2019.22241},
volume = {323},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Importance  The incremental value of polygenic risk scores in addition to well-established risk prediction models for coronary artery disease (CAD) is uncertain.Objective  To examine whether a polygenic risk score for CAD improves risk prediction beyond pooled cohort equations.Design, Setting, and Participants  Observational study of UK Biobank participants enrolled from 2006 to 2010. A case-control sample of 15947 prevalent CAD cases and equal number of age and sex frequency–matched controls was used to optimize the predictive performance of a polygenic risk score for CAD based on summary statistics from published genome-wide association studies. A separate cohort of 352660 individuals (with follow-up to 2017) was used to evaluate the predictive accuracy of the polygenic risk score, pooled cohort equations, and both combined for incident CAD.Exposures  Polygenic risk score for CAD, pooled cohort equations, and both combined.Main Outcomes and Measures  CAD (myocardial infarction and its related sequelae). Discrimination, calibration, and reclassification using a risk threshold of 7.5% were assessed.Results  In the cohort of 352660 participants (mean age, 55.9 years; 205297 women [58.2%]) used to evaluate the predictive accuracy of the examined models, there were 6272 incident CAD events over a median of 8 years of follow-up. CAD discrimination for polygenic risk score, pooled cohort equations, and both combined resulted in C statistics of 0.61 (95% CI, 0.60 to 0.62), 0.76 (95% CI, 0.75 to 0.77), and 0.78 (95% CI, 0.77 to 0.79), respectively. The change in C statistic between the latter 2 models was 0.02 (95% CI, 0.01 to 0.03). Calibration of the models showed overestimation of risk by pooled cohort equations, which was corrected after recalibration. Using a risk threshold of 7.5%, addition of the polygenic risk score to pooled cohort equations resulted in a net reclassification improvement of 4.4% (95% CI, 3.5% to 5.3%) for cases and −0.4% (95% CI, &
AU  - Elliott,J
AU  - Bodinier,B
AU  - Bond,TA
AU  - Chadeau-Hyam,M
AU  - Evangelou,E
AU  - Moons,KGM
AU  - Dehghan,A
AU  - Muller,DC
AU  - Elliott,P
AU  - Tzoulaki,I
DO  - 10.1001/jama.2019.22241
EP  - 645
PY  - 2020///
SN  - 0098-7484
SP  - 636
TI  - Predictive accuracy of a polygenic risk score-enhanced prediction model vs a clinical risk score for coronary artery disease
T2  - JAMA: Journal of the American Medical Association
UR  - http://dx.doi.org/10.1001/jama.2019.22241
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000517319500018&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://jamanetwork.com/journals/jama/fullarticle/2761088
UR  - http://hdl.handle.net/10044/1/85895
VL  - 323
ER  -
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