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Objective <p>To evaluate the discriminative power of coronary artery calcium (CAC) score–based Cox models for predicting cardiovascular disease (CVD) in older adults with longstanding diabetes, a population at elevated CVD risk. We also aimed to determine whether adding computed tomography (CT)-derived costal cartilage calcification (CCC) improves risk prediction, given the potential limitation of CAC due to widespread soft tissue calcification.</p> Materials and methods <p>We analyzed adults ≥ 65 years from the multi-ethnic study of atherosclerosis with longstanding diabetes mellitus (DM, ≥ 5 years, <i>n</i> = 231) and compared them to non-DM participants (<i>n</i> = 1148). We evaluated CAC-based risk models (adjusted for Framingham Risk Score, race/ethnicity, and statin use) and assessed the impact of adding CCC on model performance using Cox proportional-hazards regression and Harrell’s C-statistic to predict CVD and coronary heart disease (CHD) incidence. CHD events included fatal coronary events, resuscitated cardiac arrest, myocardial infarction, adjudicated angina, and revascularization with angina. CVD events encompassed CHD, stroke (excluding transient ischemic attack), cardiovascular death, or other atherosclerotic deaths.</p> Results <p>Over 8.7 years, CVD and CHD events occurred in 17% and 10% of DM participants and 11% and 5% of non-DM participants, respectively. In longstanding DM participants, doubling of CAC was associated with higher CVD risk (HR: 1.13; 95% CI: 1.01–1.26), with model discrimination improving from C-statistic 0.66 to 0.69 (<i>p</i> = 0.02) after adding CCC. For CHD, the corresponding HR was 1.05 (95% CI: 0.98–1.13), and the C-statistic rose from 0.65 to 0.69 (<i>p</i> = 0.04). In non-DM participants, CCC did not enhance model performance for either CVD or CHD (<i>p</i> &gt; 0.5).</p> Conclusion <p>CCC, a measurable biomarker of non-cardiovascular calcification from any conventional CT, improves CVD and CHD risk prediction models’ performance in older adults with longstanding DM.</p> Key Points <p><Emphasis Type="BoldItalic">Question</Emphasis> <i>Coronary artery calcium (CAC) may have limited discriminative power for predicting cardiovascular outcomes in older adults with longstanding diabetes.</i></p> <p><Emphasis Type="BoldItalic">Findings</Emphasis> <i>Costal cartilage calcification (CCC), a biomarker of non-cardiovascular calcification from CT, improves the prediction of cardiovascular disease and coronary heart disease risks in this population.</i></p> <p><Emphasis Type="BoldItalic">Clinical relevance</Emphasis> <i>Incorporating CCC, which can be easily measured using existing CAC assessment tools on CT scans, into cardiovascular risk assessment could refine clinical decision-making and improve individualized risk stratification in older adults with longstanding diabetes.</i></p> Graphical Abstract <p></p>

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Use of CT-derived non-cardiovascular calcification marker for predicting cardiovascular events among diabetic older adults: the multi-ethnic study of atherosclerosis

  • 期刊论文

  • 发表日期：

    2025年8月9日

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  • Elena Ghotbi,
  • David A. Bluemke,
  • Quincy A. Hathaway,
  • Joshua G. Klein,
  • Mahsima Shabani,
  • Sepehr Akhtarkhavari,
  • R. Graham Barr,
  • Michael P. Bancks,
  • Wendy S. Post,
  • Matthew Budoff,
  • João A. C. Lima,
  • Shadpour Demehri

摘要

Objective

To evaluate the discriminative power of coronary artery calcium (CAC) score–based Cox models for predicting cardiovascular disease (CVD) in older adults with longstanding diabetes, a population at elevated CVD risk. We also aimed to determine whether adding computed tomography (CT)-derived costal cartilage calcification (CCC) improves risk prediction, given the potential limitation of CAC due to widespread soft tissue calcification.

Materials and methods

We analyzed adults ≥ 65 years from the multi-ethnic study of atherosclerosis with longstanding diabetes mellitus (DM, ≥ 5 years, n = 231) and compared them to non-DM participants (n = 1148). We evaluated CAC-based risk models (adjusted for Framingham Risk Score, race/ethnicity, and statin use) and assessed the impact of adding CCC on model performance using Cox proportional-hazards regression and Harrell’s C-statistic to predict CVD and coronary heart disease (CHD) incidence. CHD events included fatal coronary events, resuscitated cardiac arrest, myocardial infarction, adjudicated angina, and revascularization with angina. CVD events encompassed CHD, stroke (excluding transient ischemic attack), cardiovascular death, or other atherosclerotic deaths.

Results

Over 8.7 years, CVD and CHD events occurred in 17% and 10% of DM participants and 11% and 5% of non-DM participants, respectively. In longstanding DM participants, doubling of CAC was associated with higher CVD risk (HR: 1.13; 95% CI: 1.01–1.26), with model discrimination improving from C-statistic 0.66 to 0.69 (p = 0.02) after adding CCC. For CHD, the corresponding HR was 1.05 (95% CI: 0.98–1.13), and the C-statistic rose from 0.65 to 0.69 (p = 0.04). In non-DM participants, CCC did not enhance model performance for either CVD or CHD (p > 0.5).

Conclusion

CCC, a measurable biomarker of non-cardiovascular calcification from any conventional CT, improves CVD and CHD risk prediction models’ performance in older adults with longstanding DM.

Key Points

Question Coronary artery calcium (CAC) may have limited discriminative power for predicting cardiovascular outcomes in older adults with longstanding diabetes.

Findings Costal cartilage calcification (CCC), a biomarker of non-cardiovascular calcification from CT, improves the prediction of cardiovascular disease and coronary heart disease risks in this population.

Clinical relevance Incorporating CCC, which can be easily measured using existing CAC assessment tools on CT scans, into cardiovascular risk assessment could refine clinical decision-making and improve individualized risk stratification in older adults with longstanding diabetes.

Graphical Abstract