The Multi-Ethnic Study of Atherosclerosis-Calcium Score Improves Statin Treatment Allocation in Asymptomatic Adults.

BACKGROUND

The current categorization of cardiovascular (CV) risk broadens the indications for statin therapy. Coronary artery calcium (CAC) identifies those who are most likely to benefit from primary prevention with statin therapy. The multi-ethnic study of atherosclerosis-calcium (MESA-C) includes CAC for CV risk stratification.

OBJECTIVE

We aimed to establish whether the MESA-C score improves allocation to statin treatment in a cohort of asymptomatic adults. We also analyzed patient survival according to their risk score calculation.

DESIGN

A retrospective analysis of asymptomatic adults.

PARTICIPANTS

A total of 632 consecutive subjects free of coronary artery disease (CAD) and/or stroke, mean age 56 ± 7 years, 84% male, underwent clinical evaluations and CAC measurements.

MAIN MEASURES

PCE and MESA-C risk scores were calculated for each subject. According to the 10-year risk for CV events, subjects were classified into moderate and high CV risk (≥7.5%) for whom a statin is clearly indicated, or borderline and low CV risk (<7.5%).

KEY RESULTS

During mean follow-up of 6.5 ± 3.3 years, 52 subjects experienced their first CV event. Those with a MESA-C risk score < 7.5% had favorable outcomes even when the PCE indicated a risk of ≥ 7.5%. The MESA-C score improved the discrimination of CV risk with the ROC curves C-statistics increasing from 0.653 for the PCE to 0.770 for the MESA-C. Of those, 84% (99/118) with borderline CV risk (5-7.5%) according to the PCE score, were reallocated by the MESA-C score into a higher (≥7.5%) or lower (<5%) CV risk category. Furthermore, subjects with low MESA-C scores had the highest survival rate regardless of the PCE risk, while those with high MESA-C risks had the lowest survival rate regardless of the PCE risk.

CONCLUSION

In asymptomatic subjects, the MESA-C score improves allocation to statin treatment and CV risk discrimination, while both scores are essential for more precise survival estimations.