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Novel genetic markers improve measures of atrial fibrillation risk prediction
AIMS: Atrial fibrillation (AF) is associated with adverse outcome. Whether recently discovered genetic risk markers improve AF risk prediction is unknown. METHODS AND RESULTS: We derived and validated a novel AF risk prediction model from 32 possible predictors in the Women's Health Study (WHS)...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3730133/ https://www.ncbi.nlm.nih.gov/pubmed/23444395 http://dx.doi.org/10.1093/eurheartj/eht033 |
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author | Everett, Brendan M. Cook, Nancy R. Conen, David Chasman, Daniel I. Ridker, Paul M Albert, Christine M. |
author_facet | Everett, Brendan M. Cook, Nancy R. Conen, David Chasman, Daniel I. Ridker, Paul M Albert, Christine M. |
author_sort | Everett, Brendan M. |
collection | PubMed |
description | AIMS: Atrial fibrillation (AF) is associated with adverse outcome. Whether recently discovered genetic risk markers improve AF risk prediction is unknown. METHODS AND RESULTS: We derived and validated a novel AF risk prediction model from 32 possible predictors in the Women's Health Study (WHS), a cohort of 20 822 women without cardiovascular disease (CVD) at baseline followed prospectively for incident AF (median: 14.5 years). We then created a genetic risk score (GRS) comprised of 12 risk alleles in nine loci and assessed model performance in the validation cohort with and without the GRS. The newly derived WHS AF risk algorithm included terms for age, weight, height, systolic blood pressure, alcohol use, and smoking (current and past). In the validation cohort, this model was well calibrated with good discrimination [C-index (95% CI) = 0.718 (0.684–0.753)] and improved all reclassification indices when compared with age alone. The addition of the genetic score to the WHS AF risk algorithm model improved the C-index [0.741 (0.709–0.774); P = 0.001], the category-less net reclassification [0.490 (0.301–0.670); P < 0.0001], and the integrated discrimination improvement [0.00526 (0.0033–0.0076); P < 0.0001]. However, there was no improvement in net reclassification into 10-year risk categories of <1, 1–5, and 5+% [0.041 (−0.044–0.12); P = 0.33]. CONCLUSION: Among women without CVD, a simple risk prediction model utilizing readily available risk markers identified women at higher risk for AF. The addition of genetic information resulted in modest improvements in predictive accuracy that did not translate into improved reclassification into discrete AF risk categories. |
format | Online Article Text |
id | pubmed-3730133 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-37301332013-08-01 Novel genetic markers improve measures of atrial fibrillation risk prediction Everett, Brendan M. Cook, Nancy R. Conen, David Chasman, Daniel I. Ridker, Paul M Albert, Christine M. Eur Heart J Clinical Research AIMS: Atrial fibrillation (AF) is associated with adverse outcome. Whether recently discovered genetic risk markers improve AF risk prediction is unknown. METHODS AND RESULTS: We derived and validated a novel AF risk prediction model from 32 possible predictors in the Women's Health Study (WHS), a cohort of 20 822 women without cardiovascular disease (CVD) at baseline followed prospectively for incident AF (median: 14.5 years). We then created a genetic risk score (GRS) comprised of 12 risk alleles in nine loci and assessed model performance in the validation cohort with and without the GRS. The newly derived WHS AF risk algorithm included terms for age, weight, height, systolic blood pressure, alcohol use, and smoking (current and past). In the validation cohort, this model was well calibrated with good discrimination [C-index (95% CI) = 0.718 (0.684–0.753)] and improved all reclassification indices when compared with age alone. The addition of the genetic score to the WHS AF risk algorithm model improved the C-index [0.741 (0.709–0.774); P = 0.001], the category-less net reclassification [0.490 (0.301–0.670); P < 0.0001], and the integrated discrimination improvement [0.00526 (0.0033–0.0076); P < 0.0001]. However, there was no improvement in net reclassification into 10-year risk categories of <1, 1–5, and 5+% [0.041 (−0.044–0.12); P = 0.33]. CONCLUSION: Among women without CVD, a simple risk prediction model utilizing readily available risk markers identified women at higher risk for AF. The addition of genetic information resulted in modest improvements in predictive accuracy that did not translate into improved reclassification into discrete AF risk categories. Oxford University Press 2013-08-01 2013-02-26 /pmc/articles/PMC3730133/ /pubmed/23444395 http://dx.doi.org/10.1093/eurheartj/eht033 Text en © The Author 2013. Published by Oxford University Press on behalf of the European Society of Cardiology. http://creativecommons.org/licenses/by-nc/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial use, distribution, and reproduction in any medium, provided that the original authorship is properly and fully attributed; the Journal, Learned Society and Oxford University Press are attributed as the original place of publication with correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Clinical Research Everett, Brendan M. Cook, Nancy R. Conen, David Chasman, Daniel I. Ridker, Paul M Albert, Christine M. Novel genetic markers improve measures of atrial fibrillation risk prediction |
title | Novel genetic markers improve measures of atrial fibrillation risk prediction |
title_full | Novel genetic markers improve measures of atrial fibrillation risk prediction |
title_fullStr | Novel genetic markers improve measures of atrial fibrillation risk prediction |
title_full_unstemmed | Novel genetic markers improve measures of atrial fibrillation risk prediction |
title_short | Novel genetic markers improve measures of atrial fibrillation risk prediction |
title_sort | novel genetic markers improve measures of atrial fibrillation risk prediction |
topic | Clinical Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3730133/ https://www.ncbi.nlm.nih.gov/pubmed/23444395 http://dx.doi.org/10.1093/eurheartj/eht033 |
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