Adding ethnicity to cardiovascular risk prediction: External validation and model updating of SCORE2 using data from the HELIUS population cohort

Abstract

BACKGROUND: Current prediction models for mainland Europe do not include ethnicity, despite ethnic disparities in cardiovascular disease (CVD) risk. SCORE2 performance was evaluated across the largest ethnic groups in the Netherlands and ethnic backgrounds were added to the model. METHODS: 11,614 participants, aged between 40 and 70 years without CVD, from the population-based multi-ethnic HELIUS study were included. Fine and Gray models were used to calculate sub-distribution hazard ratios (SHR) for South-Asian Surinamese, African Surinamese, Ghanaian, Turkish and Moroccan origin groups, representing their CVD risk relative to the Dutch group, on top of individual SCORE2 risk predictions. Model performance was evaluated by discrimination, calibration and net reclassification index (NRI). RESULTS: Overall, 274 fatal and non-fatal CVD events, and 146 non-cardiovascular deaths were observed during a median of 7.8 years follow-up (IQR 6.8-8.8). SHRs for CVD events were 1.86 (95 % CI 1.31-2.65) for the South-Asian Surinamese, 1.09 (95 % CI 0.76-1.56) for the African-Surinamese, 1.48 (95 % CI 0.94-2.31) for the Ghanaian, 1.63 (95 % CI 1.09-2.44) for the Turkish, and 0.67 (95 % CI 0.39-1.18) for the Moroccan origin groups. Adding ethnicity to SCORE2 yielded comparable calibration and discrimination [0.764 (95 % CI 0.735-0.792) vs. 0.769 (95 % CI 0.740-0.797)]. The NRI for adding ethnicity to SCORE2 was 0.24 (95 % CI 0.18-0.31) for events and - 0.12 (95 % CI -0.13-0.12) for non-events. CONCLUSIONS: Adding ethnicity to the SCORE2 risk prediction model in a middle-aged, multi-ethnic Dutch population did not improve overall discrimination but improved risk classification, potentially helping to address CVD disparities through timely treatment.