External validation of the SMART2 model for recurrent cardiovascular risk: performance in socioeconomic, ethnic and psychiatric subgroups

Abstract

BACKGROUND: Secondary prevention is critical for patients with established atherosclerotic cardiovascular diseases (ASCVD). The SMART2 model predicts recurrent ASCVD risk but does not account for psychiatric disorders, socioeconomic deprivation or ethnicity. We aimed to evaluate SMART2 model performance overall and in subgroups defined by these factors. METHODS: SMART2 was externally validated using electronic health records of patients aged 40-80 in the Leiden-The Hague region. Patients hospitalised for cardiovascular disease or coronary interventions between 1 January 2010 and 31 December 2021 were included. Model performance was assessed using discrimination (10-year area under ROC curve (AUC)) and calibration (observed/expected (OE) ratios and plots, adjusted for competing risks), both overall and in subgroups defined by three factors: psychiatric history, socioeconomic status (SES) and ethnicity. RESULTS: Among 15 528 patients (66% male, mean age 65) with established ASCVD, median follow-up was 6.0 years. Recurrent cardiovascular events occurred in 2220 patients, and 1820 had competing events. Overall AUC was 0.63 (95% CI 0.61 to 0.65). OE ratio was 0.96 (95% CI 0.92 to 1.00). The model underestimated risk in patients with low SES (OE 1.09, 95% CI 1.02 to 1.17) and in non-Western patients (OE 1.16, 95% CI 1.02 to 1.31). Calibration was adequate in patients with psychiatric history, but the model was substantially underestimating for patients with multiple vulnerabilities-combinations of low SES, non-Western ethnicity and psychiatric history-with OE ranging from 1.19 to 1.29, depending on the combination. CONCLUSION: The SMART2 model is well-calibrated in the general population but underestimates risk, especially in subgroups with multiple vulnerabilities. Patients in these vulnerable subgroups may require intensified monitoring. Clinicians should consider social, ethnic and psychiatric factors when interpreting risk estimates.