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. 2009 Mar;40(3 Suppl):S67-70.
doi: 10.1161/STROKEAHA.108.533273. Epub 2008 Dec 8.

Predictive genomics of cardioembolic stroke

Rachel Badovinac Ramoni  1 , Blanca E Himes, Michele M Sale, Karen L Furie, Marco F Ramoni
Affiliations

Predictive genomics of cardioembolic stroke

Rachel Badovinac Ramoni et al. Stroke. 2009 Mar.

Abstract

Cardioembolic stroke is a complex disease resulting from the interaction of numerous factors. Using data from Genes Affecting Stroke Risk and Outcome Study (GASROS), we show that a multivariate predictive model built using Bayesian networks is able to achieve a predictive accuracy of 86% on the fitted values as computed by the area under the receiver operating characteristic curve relative to that of the individual single nucleotide polymorphism with the highest prognostic performance (area under the receiver operating characteristic curve=60%).

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Figures

Figure 1
Figure 1
Bayesian network describing the joint association for 37 SNPs (blue) and race (pink) with the risk of cardioembolic stroke (red).
Figure 2
Figure 2
ROC curve measuring the predictive accuracy of the Bayesian network in Figure 1 on the fitted values. The curve extending from the origin at 45 degrees represents random classification with an area under the ROC of 50%. Also shown is the ROC curve corresponding to the Bayesian network (area under the ROC=86.0%), bounded by its 95% CI.
See this image and copyright information in PMC

References

    1. Thom T, Haase N, Rosamond W, Howard VJ, Rumsfeld J, Manolio T, Zheng ZJ, Flegal K, O’Donnell C, Kittner S, Lloyd-Jones D, Goff DC, Jr, Hong Y, Adams R, Friday G, Furie K, Gorelick P, Kissela B, Marler J, Meigs J, Roger V, Sidney S, Sorlie P, Steinberger J, Wasserthiel-Smoller S, Wilson M, Wolf P American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Heart disease and stroke statistics—2006 update: a report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Circulation. 2006;113:e85–e151. - PubMed
    1. Markus HS, Khan U, Birns J, Evans A, Kalra L, Rudd AG, Wolfe CD, Jerrard-Dunne P. Differences in stroke subtypes between black and white patients with stroke: the South London Ethnicity and Stroke study. Circulation. 2007;116:2157–2164. - PubMed
    1. White H, Boden-Albala B, Wang C, Elkind MS, Rundek T, Wright CB, Sacco RL. Ischemic stroke subtype incidence among whites, blacks, and Hispanics: the Northern Manhattan Study. Circulation. 2005;111:1327–1331. - PubMed
    1. Bersano A, Ballabio E, Bresolin N, Candelise L. Genetic polymorphisms for the study of multifactorial stroke. Hum Mutat. 2008;29:776–795. - PubMed
    1. Di Napoli M. How to search for the role of genetic polymorphisms in stroke: theory versus practice. Stroke. 2003;34:1869–1870. - PubMed

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