SCORE2-Diabetes: 10-year cardiovascular risk estimation in type 2 diabetes in Europe

Abstract

Aims: To develop and validate a recalibrated prediction model (SCORE2-Diabetes) to estimate the 10-year risk of cardiovascular disease (CVD) in individuals with type 2 diabetes in Europe.

Methods and results: SCORE2-Diabetes was developed by extending SCORE2 algorithms using individual-participant data from four large-scale datasets comprising 229 460 participants (43 706 CVD events) with type 2 diabetes and without previous CVD. Sex-specific competing risk-adjusted models were used including conventional risk factors (i.e. age, smoking, systolic blood pressure, total, and HDL-cholesterol), as well as diabetes-related variables (i.e. age at diabetes diagnosis, glycated haemoglobin [HbA1c] and creatinine-based estimated glomerular filtration rate [eGFR]). Models were recalibrated to CVD incidence in four European risk regions. External validation included 217 036 further individuals (38 602 CVD events), and showed good discrimination, and improvement over SCORE2 (C-index change from 0.009 to 0.031). Regional calibration was satisfactory. SCORE2-Diabetes risk predictions varied several-fold, depending on individuals' levels of diabetes-related factors. For example, in the moderate-risk region, the estimated 10-year CVD risk was 11% for a 60-year-old man, non-smoker, with type 2 diabetes, average conventional risk factors, HbA1c of 50 mmol/mol, eGFR of 90 mL/min/1.73 m2, and age at diabetes diagnosis of 60 years. By contrast, the estimated risk was 17% in a similar man, with HbA1c of 70 mmol/mol, eGFR of 60 mL/min/1.73 m2, and age at diabetes diagnosis of 50 years. For a woman with the same characteristics, the risk was 8% and 13%, respectively.

Conclusion: SCORE2-Diabetes, a new algorithm developed, calibrated, and validated to predict 10-year risk of CVD in individuals with type 2 diabetes, enhances identification of individuals at higher risk of developing CVD across Europe.

Keywords: Cardiovascular diseases; Diabetes; Prediction model.

Structured Graphical Abstract

SCORE2-Diabetes 10-year CVD risk models: development process, key features and illustrative example. CVD: cardiovascular disease; SBP: systolic blood pressure; HDL-C: high-density lipoprotein cholesterol; HbA1c (mmol/mol): glycated haemoglobin, in International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) units; eGFR: estimated Glomerular Filtration Rate (mL/min/1.73m²).

Figure 1

Study design for the SCORE2-Diabetes project. ERFC: Emerging Risk Factors Collaboration, CPRD: Clinical Practice Research Datalink, SCID: Scottish Care Information—Diabetes, SNDR: Swedish National Diabetes Register, SIDIAP: Sistema d'Informació per al Desenvolupament de la Investigació en Atenció Primària, EUBIROD: EUropean Best Information through Regional Outcome in Diabetes, eGFR: estimated Glomerular Filtration Rate, HbA1c: glycated haemoglobin.

Figure 2

Internal and External validation of the SCORE2-Diabetes models: ability to discriminate CVD risk. CPRD: Clinical Practice Research Datalink; ERFC: Emerging Risk Factors Collaboration; UKB: UK Biobank; SCID: Scottish Care Information—Diabetes; SIDIAP: Sistema d'Informació per al Desenvolupament de la Investigació en Atenció Primària; SNDR: Swedish National Diabetes Register.

Figure 3

Estimates are for non-smokers with systolic blood pressure of 140 mm Hg, total cholesterol of 5.5 mmol/L and HDL-cholesterol of 1.3 mmol/L. eGFR: estimated Glomerular Filtration Rate (mL/min/1.73 m²) calculated using the CKD-EPI 2009 equations; HbA1c (mmol/mol): glycated haemoglobin, in International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) units.

Figure 4

The proportion of individuals expected in each risk category was estimated to reflect the age-group and sex-specific risk factor values in each risk region (see Supplementary data online, Supplementary methods).