Bríain Ó Hartaigh1, Valentina Valenti1, Iksung Cho1, Joshua Schulman-Marcus1, Heidi Gransar2, Joseph Knapper3, Anita A Kelkar3, Joseph X Xie3, Hyuk-Jae Chang4, Leslee J Shaw3, Tracy Q Callister5, James K Min6. 1. Department of Radiology and Medicine, Dalio Institute of Cardiovascular Imaging, NewYork-Presbyterian Hospital/Weill Cornell Medical College, New York, NY, USA. 2. Department of Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA. 3. Department of Medicine, Division of Cardiology, Emory University School of Medicine, Atlanta, GA, USA. 4. Division of Cardiology, Severance Cardiovascular Hospital and Severance Biomedical Science Institute, Yonsei University College of Medicine, Yonsei University Health System, Seoul, South Korea. 5. Tennessee Heart and Vascular Institute, Hendersonville, TN, USA. 6. Department of Radiology and Medicine, Dalio Institute of Cardiovascular Imaging, NewYork-Presbyterian Hospital/Weill Cornell Medical College, New York, NY, USA. Electronic address: jkm2001@med.cornell.edu.
Abstract
INTRODUCTION: Prior studies have demonstrated a decline in the predictive ability of conventional risk factors (RF) with advancing age, emphasizing the need for novel tools to improve risk stratification in the elderly. Coronary artery calcification (CAC) is a robust predictor of adverse cardiovascular events, but its long-term prognostic utility beyond RFs in elderly persons is unknown. METHODS: A consecutive series of 9715 individuals underwent CAC scoring and were followed for a mean of 14.6 ± 1.1 years. Multivariable Cox proportional hazards regression (HR) with 95% confidence intervals (95% CI) was employed to assess the independent relationship of CAC and RFs with all-cause death. The incremental value of CAC, stratified by age, was examined by using an area under the receiver operator characteristic curve (AUC) and category-free net reclassification improvement (NRI). RESULTS: Of the overall study sample, 728 (7.5%) adults (mean age 74.2 ± 4.2 years; 55.6% female) were 70 years or older, of which 157 (21.6%) died. The presence of any CAC was associated with a >4-fold (95% CI = 2.84-6.59) adjusted risk of death for those over the age of 70, which was higher compared with younger study counterparts, or other measured RFs. For individuals 70 years or older, the discriminatory ability of CAC improved upon that of RFs alone (C statistics 0.764 vs. 0.675, P < 0.001). CAC also enabled improved reclassification (category-free NRI = 84%, P < 0.001) when added to RFs. CONCLUSION: In a large-scale observational cohort registry, CAC improves prediction, discrimination, and reclassification of elderly individuals at risk for future death.
INTRODUCTION: Prior studies have demonstrated a decline in the predictive ability of conventional risk factors (RF) with advancing age, emphasizing the need for novel tools to improve risk stratification in the elderly. Coronary artery calcification (CAC) is a robust predictor of adverse cardiovascular events, but its long-term prognostic utility beyond RFs in elderly persons is unknown. METHODS: A consecutive series of 9715 individuals underwent CAC scoring and were followed for a mean of 14.6 ± 1.1 years. Multivariable Cox proportional hazards regression (HR) with 95% confidence intervals (95% CI) was employed to assess the independent relationship of CAC and RFs with all-cause death. The incremental value of CAC, stratified by age, was examined by using an area under the receiver operator characteristic curve (AUC) and category-free net reclassification improvement (NRI). RESULTS: Of the overall study sample, 728 (7.5%) adults (mean age 74.2 ± 4.2 years; 55.6% female) were 70 years or older, of which 157 (21.6%) died. The presence of any CAC was associated with a >4-fold (95% CI = 2.84-6.59) adjusted risk of death for those over the age of 70, which was higher compared with younger study counterparts, or other measured RFs. For individuals 70 years or older, the discriminatory ability of CAC improved upon that of RFs alone (C statistics 0.764 vs. 0.675, P < 0.001). CAC also enabled improved reclassification (category-free NRI = 84%, P < 0.001) when added to RFs. CONCLUSION: In a large-scale observational cohort registry, CAC improves prediction, discrimination, and reclassification of elderly individuals at risk for future death.
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