SCORE2 risk prediction algorithms to estimate 10-year risk of cardiovascular disease in Europe

SCORE2 - a new algorithm derived, calibrated, and validated to predict 10-year risk of first-onset CVD in European populations- enhances the identification of individuals at higher risk of developing CVD across Europe (1)

• derived risk prediction models using individual-participant data from 45 cohorts in 13 countries (677684 individuals, 30121 CVD events)
  • used sex-specific and competing risk-adjusted models, including age, smoking status, systolic blood pressure, and total- and HDL-cholesterol
  • defined four risk regions in Europe according to country-specific CVD mortality, recalibrating models to each region using expected incidences and risk factor distributions
  • region-specific incidence was estimated using CVD mortality and incidence data on 10776466 individuals
  • for external validation
    • analysed data from 25 additional cohorts in 15 European countries (1133181 individuals, 43492 CVD events)
    • after applying the derived risk prediction models to external validation cohorts, C-indices ranged from 0.67 (0.65-0.68) to 0.81 (0.76-0.86)
    • predicted CVD risk varied several-fold across European regions
      • for example, the estimated 10-year CVD risk for a 50 year old smoker, with a systolic blood pressure of 140mmHG, total cholesterol of 5.5 mmol/L, and HDL-cholesterol of 1.3 mmol/L, ranged from 5.9% for men in low-risk countries to 14% for men in very high-risk countries, and from 4.2% for women in low-risk countries to 13.7% for women in very high-risk countries
• Key points:
  
  
  • SCORE2 provides risk estimates for the combined outcome of fatal and non-fatal CVD events, in contrast with SCORE's use of CVD mortality only
    
    
  • SCORE2 accounts for the impact of competing risks by non-CVD deaths whereas SCORE did not do so
    
    
  • the recalibration of SCORE2 to four distinct European regions defined by varying CVD risk levels improves on the two-level regional stratification provided by SCORE
    • furthermore, as the recalibration used for SCORE2 avoids reliance on sparse cohort or country-level data, it provides recalibrated calculators tailored to sex-specific CVD rates and risk factor levels of each region
    • because the recalibration approach we used is based on registry data, the model can be readily updated to reflect future disease CVD incidence and risk factor profiles of any target population of apparently healthy individuals to be screened

Notes:

• data on medication use, family history, socio-economic status, nutrition, physical activity, renal function, or ethnicity were not available in cohorts and registries used for model derivation and recalibration
  • therefore interpretation of SCORE2 estimates may require clinical judgement, especially for individuals in whom these factors may be relevant (e.g. those taking lipid or blood pressure-lowering treatments,with a family history of CVD,with chronic kidney disease,or in at-risk socio-economic and ethnic groups)
  • some individuals in the model derivation cohorts may have initiated preventative treatment (e.g. statin) during follow-up and accounting for this could improve model calibration and discrimination. However, previous analyses have suggested that inclusion of information on statin-initiation during follow-up provides only limited clinical and public health benefit (1)
• the study authors did not compare the performance of SCORE2 models with other risk equations already developed for use in specific high-income countries because these equations contain variables often not available in European datasets used for derivation and recalibration

Reference:

1. SCORE2 working group and ESC Cardiovascular risk collaboration. SCORE2 risk prediction algorithms: new models to estimate 10-year risk of cardiovascular disease in Europe. Eur Heart J. 2021 Jun 13:ehab309. doi: 10.1093/eurheartj/ehab309