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A Model for Predicting the Risk of Carotid Artery Disease

Greco, Giampaolo PhD*; Egorova, Natalia Nickolayevna PhD*; Moskowitz, Alan Jay MD*; Gelijns, Annetine Christine PhD*; Kent, K. Craig MD†,‡; Manganaro, Andrew Joseph MD†,§; Zwolak, Robert Matthew MD†,‖; Riles, Thomas Stewart MD†,¶

doi: 10.1097/SLA.0b013e31827b9761
Original Articles

Objective: To develop a model for the identification of individuals at risk for carotid stenosis (CS) that could be useful in a clinical setting when trying to decide whether screening is worthwhile.

Background: Evidence that aggressive medical therapy and life style changes reduce the risk of stroke in individuals with CS is increasing and has led to a renewed interest in screening for CS.

Methods: Data on demographics and risk factors were obtained from 2,885,257 individuals who had carotid Duplex scans by Life Line Screening between 2003 and 2008. Multivariable logistic regression analysis was used to identify independent risk factors for CS (>50% stenosis). A scoring system was developed where risk factors were assigned a weighted score. Predictive ability was assessed by calculating C statistics and r 2.

Results: In the screened cohort, 71,004 patients (2.4%) had CS. Independent risk factors include advanced age, smoking, peripheral arterial disease, high blood pressure, coronary artery disease, diabetes, cholesterol, and abdominal aortic aneurysm. African Americans, Asians, and Hispanics had reduced risk than whites. Exercise and consumption of fruit, vegetables, and nuts had a modest protective effect. A predictive scoring system was created that identifies individuals with CS more efficiently (C statistic = 0.753) than previously published models.

Conclusions: We provide a model that enables identification of individuals who have a high probability of having CS. This model can be helpful in designing targeted screening programs that are cost-effective.

Increasing evidence that aggressive medical therapy can reduce the risk of stroke has renewed the interest in screening for carotid stenosis. Using a database from about 3 million screened individuals, we developed a model to predict the probability of having carotid artery disease.

*Department of Health Evidence and Policy, Mount Sinai School of Medicine, New York, NY

The Society for Vascular Surgery (SVS) Screening Task Force, SVS, Chicago, IL

Department of Surgery, University of Wisconsin, Madison, WI

§Life Line Screening, Independence, OH

Department of Vascular Surgery, Dartmouth-Hitchcock Medical Center, Lebanon, NH

Department of Surgery, NYU Langone Medical Center, New York, NY.

Reprints: Giampaolo Greco, PhD, MPH, Department of Health Evidence and Policy, Mount Sinai School of Medicine, One Gustave L. Levy Place, Box 1077, New York, NY 10029. E-mail:

Disclosure: Dr. Manganaro, the chief medical officer and a salaried employee of Life Line Screening, reports no financial gain or any other material benefits from this publication. For the remaining authors, no conflicts of interest weredeclareed. This study was funded in part by a grant to the Society for Vascular Surgery from Life Line Screening, Independence, OH. The Society for Vascular Surgery provided a grant to the department of Health Evidence and Policy at Mount Sinai School of Medicine to be the data-coordinating center for this project.

© 2013 Lippincott Williams & Wilkins, Inc.