10-Year Coronary Heart Disease Risk Prediction Using Coronary Artery Calcium and Traditional Risk Factors
Derivation in the MESA (Multi-Ethnic Study of Atherosclerosis) With Validation in the HNR (Heinz Nixdorf Recall) Study and the DHS (Dallas Heart Study)
Robyn L. McClelland, PHD; Neal W. Jorgensen, MS; Matthew Budoff, MD; Michael J. Blaha, MD, MPH; Wendy S. Post, MD, MS; Richard A. Kronmal, PHD; Diane E. Bild, MD, MPH; Steven Shea, MD, MS; Kiang Liu, PHD; Karol E. Watson, MD, PHD; Aaron R. Folsom, MD; Amit Khera, MD; Colby Ayers, MS; Amir-Abbas Mahabadi, MD; Nils Lehmann, PHD; Karl-Heinz Jöckel, PHD; Susanne Moebus, PHD; J. Jeffrey Carr, MD, MS; Raimund Erbel, MD, PHD; Gregory L. Burke, MD, MS
J Am Coll Cardiol. 2015;66(15):1643-1653.
Abstract and Introduction
Methods
Results
Discussion
Conclusions
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Abstract and Introduction
Abstract
Background Several studies have demonstrated the tremendous potential of using coronary artery calcium (CAC) in addition to traditional risk factors for coronary heart disease (CHD) risk prediction. However, to date, no risk score incorporating CAC has been developed.
Objectives The goal of this study was to derive and validate a novel risk score to estimate 10-year CHD risk using CAC and traditional risk factors.
Methods Algorithm development was conducted in the MESA (Multi-Ethnic Study of Atherosclerosis), a prospective community-based cohort study of 6,814 participants age 45 to 84 years, who were free of clinical heart disease at baseline and followed for 10 years. MESA is sex balanced and included 39% non-Hispanic whites, 12% Chinese Americans, 28% African Americans, and 22% Hispanic Americans. External validation was conducted in the HNR (Heinz Nixdorf Recall Study) and the DHS (Dallas Heart Study).
Results Inclusion of CAC in the MESA risk score offered significant improvements in risk prediction (C-statistic 0.80 vs. 0.75; p [ 0.0001). External validation in both the HNR and DHS studies provided evidence of very good discrimination and calibration. Harrell’s C-statistic was 0.779 in HNR and 0.816 in DHS. Additionally, the difference in estimated 10-year risk between events and nonevents was approximately 8% to 9%, indicating excellent discrimination. Mean calibration, or calibration-in-the-large, was excellent for both studies, with average predicted 10-year risk within one-half of a percent of the observed event rate.
Conclusions An accurate estimate of 10-year CHD risk can be obtained using traditional risk factors and CAC. The MESA risk score, which is available online on the MESA web site for easy use, can be used to aid clinicians when communicating risk to patients and when determining risk-based treatment strategies.
Introduction
Coronary artery calcium (CAC) scores derived from routine cardiac-gated noncontrast computed tomography scans are a commonly used method for enhancing clinical cardiovascular risk prediction. Importantly, CAC scores are incremental but not redundant with traditional risk factors, and therefore, integration of both sets of information can enhance risk assessment. Indeed, the added value of CAC over and above traditional risk factors for prediction of cardiovascular events has been demonstrated in several studies.[1–11] However, to date, no published risk scores are available to clinicians to incorporate CAC into routine 10-year risk prediction.
The MESA (Multi-Ethnic Study of Atherosclerosis), due to its population-based, multiethnic composition and availability of 10 years of follow-up for incident CHD events, provides a unique opportunity to describe how CAC might be optimally combined with traditional risk factors in risk prediction. In this paper, we describe a novel MESA risk score that can be used to estimate 10-year CHD risk in patients with a CAC measurement. We also provide a score without inclusion of CAC for evaluation of the effect of including CAC in the novel risk score. We believe that the MESA risk score could be immediately used for communication of risk with patients after CAC scoring, to guide risk-based treatment decisions in clinical practice, as well as in designing future research studies that might use CAC to target high-risk subpopulations.
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