Key result
Higher carotid plaque score linked to ~32% higher 5-year MACE risk per point.
Why the study?
The incremental predictive value of a simplified six-segment carotid plaque score within a multivariable MACE risk model was not well characterized in hospital-based Chinese primary-prevention populations.
Does incorporating a simplified 0-6 six-segment carotid plaque score into a multivariable clinical prediction model improve 5-year hard MACE risk prediction compared to conventional clinical predictors alone or with binary plaque presence in hospital-based primary-prevention adults?
Cohort (n=2,413)
Blinded outcome adjudication
No
Does incorporating a simplified 0-6 six-segment carotid plaque score into a multivariable clinical prediction model improve 5-year hard MACE risk prediction compared to conventional clinical predictors alone or with binary plaque presence in hospital-based primary-prevention adults?
Adding a pragmatic 0-6 segment-based carotid plaque score to conventional clinical risk factors significantly improves 5-year MACE discrimination and clinical net benefit in hospital-based primary prevention patients undergoing carotid ultrasound.
May enhance MACE risk stratification in models; extends plaque markers but leaves open prospective validation.
Background Carotid plaque burden is an established cardiovascular risk marker, but the incremental predictive value of a simplified six-segment plaque score within a multivariable model remains less well characterized in hospital-based Chinese primary-prevention populations. We aimed to develop and internally validate a 5-year model for major adverse cardiovascular and cerebrovascular events (MACE) incorporating this score. Methods This single-center retrospective cohort included adults aged ≥40 years without prior clinical cardiovascular or cerebrovascular disease who underwent bilateral carotid ultrasonography between 2015 and 2020. Plaque presence in six carotid segments generated a 0–6 score. The primary outcome was 5-year hard MACE, defined as cardiovascular death, nonfatal myocardial infarction, or nonfatal ischemic stroke. Three Cox models were compared: clinical predictors alone, clinical predictors plus binary plaque presence, and clinical predictors plus plaque score. Performance was assessed by discrimination, calibration, Brier score, decision curve analysis, and 1,000 bootstrap resamples. Results Among 2,413 patients, 1,560 (64.6%) had carotid plaque and 108 experienced hard MACE during a median follow-up of 4.92 years. Five-year MACE incidence increased from 1.5% for plaque scores 0–1 to 6.1% for scores 2–4 and 15.4% for scores 5–6 ( P < 0.001). Each 1-point score increase was associated with higher MACE risk (HR, 1.32; 95% CI, 1.21–1.44). The apparent C-index increased from 0.753 for the clinical model to 0.804 with the plaque score; the corresponding 5-year AUC and Brier score were 0.807 and 0.0381. After bootstrap correction, the C-index was 0.792 and calibration slope 0.93. Model 3 showed greater net benefit across most 2%–10% thresholds, with broadly similar findings in sensitivity analyses. Conclusions In this hospital-based primary-prevention cohort, the simplified six-segment carotid plaque score provided incremental predictive information beyond conventional clinical factors and binary plaque presence. External validation, particularly in lower-risk community and primary-care populations, is required before broader clinical application.
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Hu et al. (2026) conducted a cohort in Primary prevention of cardiovascular and cerebrovascular disease (subclinical carotid atherosclerosis) (n=2,413). Simplified six-segment carotid plaque score (0–6 scale, per 1-point increase) vs. Conventional clinical predictors alone or plus binary carotid plaque presence was evaluated on 5-year hard major adverse cardiovascular and cerebrovascular events (MACE: cardiovascular death, non-fatal myocardial infarction, or non-fatal ischemic stroke) (HR 1.32, 95% CI 1.21-1.44, p=<0.001). Each 1-point increase in the 0–6 carotid plaque score increased 5-year MACE risk (HR 1.32, 95% CI 1.21–1.44) and improved model discrimination from C-index 0.753 to 0.804.
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