Validation of the SCORE2 risk prediction algorithm in a Portuguese population: A new model to estimate 10-year cardiovascular disease incidence in Europe

Introduction and objectives: Subjects without cardiovascular (CV) disease (CVD) may suffer from subclinical atherosclerosis, and are at increased risk for atherosclerotic CV events (ASCVE). The ESC/EAS risk SCORE was updated by SCORE2, which estimates 10-year risk of fatal and non-fatal CVD in European populations aged 40-69 years without established CVD or diabetes. Our aim was to compare the two ESC/EAS risk scores and to validate SCORE2 in our population.

Methods: A total of 1071 individuals (age 57.2±6.1 years; 75.2% male) without CVD or diabetes, from GENEMACOR study controls, were analyzed over 5.4±3.9 years. The population was stratified into risk categories according to the two scores, and the area under the ROC curve (AUC) and Harrell's C-index assessed the scores' performance. Calibration was performed using the goodness-of-fit test, and occurrence of the first event assessed by Cox regression. Kaplan-Meier analysis estimated SCORE2 survival.

Results: SCORE stratified subjects into four risk categories: low (7.4%), moderate (46.5%), high (25.3%) and very high (20.8%), and SCORE2 into three: low-to-moderate (24.7%), high (59.0%) and very high (16.2%). SCORE presented good discrimination for CV mortality (AUC=0.838; C-index=0.834, 95% CI: 0.728-0.940), as did SCORE2 for total CV events (AUC=0.744; C-index=0.728, 95% CI: 0.648-0.808). Calibration did not show a disparity between observed and expected ASCVE. The probability of ASCVE was eight times higher in very-high-risk SCORE2 (p=0.001), and three times in the high-risk group (p=0.049). Event-free survival was 99%, 90% and 72% in the low-to-moderate, high and very-high-risk categories, respectively (p<0.0001).

Conclusions: SCORE2 improved population stratification by identifying higher-risk patients, enabling early preventive measures. It showed good discriminative ability for all ASCVE.