SCORE 2D predicts risk of cardiovascular disease in patients with diabetes

By Dr. Priyom Bose, Ph.D.Reviewed by Benedette Cuffari, M.Sc.Jun 15 2023

Although several predictive models have been developed to predict cardiovascular (CV) disease risks, none have considered diabetes as a risk factor that may influence the incidence of CV disease.

Study: Risk prediction in patients with diabetes: Is SCORE 2D the perfect solution? Image Credit: NicoElNino / Shutterstock.com

Background

Previous epidemiological studies have revealed that increasing age, as well as the prevalence of hyperlipidemia, hypertension, smoking, and other factors, increases the risk of CV disease. In addition to individuals with these health conditions, CV prevention remains equally important for patients without these diseases, as several other factors could synergistically act to enhance the risk of CV diseases. 

In 1994, the first European guidelines on the prevention of coronary heart disease were developed. However, this guideline was associated with many limitations, particularly due to the lack of accurate data and that the available data was based on the Framingham study, which restricted its applicability to a diverse population.

In 2003, a new European risk chart known as the Systematic Coronary Risk Evaluation (SCORE) was developed using large-scale data from 12 large European cohort studies. Despite these improvements, SCORE only predicted deaths due to CV disease without providing information about stroke and non-fatal myocardial infarction.

In an effort to overcome these limitations, the most recent version of SCORE 2 was launched in 2021. In addition to incorporating data from 45 European cohort studies on stroke, myocardial infarction, and CV mortality, SCORE 2 also provided information on risk factor distribution within the population.

The models used to develop SCORE 2 were validated based on data from more than one million participants from 15 European countries. Considering the differential rate of CV diseases across Europe, SCORE and SCORE 2 developed separate risk charts for each region that were characterized as low, high, and very high. 

One limitation of SCORE and SCORE 2 is that neither of these guidelines considers diabetes (DM) among CV mortality risk factors. Therefore, SCORE and SCORE 2 are only applicable to people without DM.

Most adults with type 2 diabetes are at high or very high risk for future CV disease, particularly from middle age onwards. On average, type 2 DM doubles CV disease risk and reduces life expectancy by four to six years, with absolute risks highest in those with any target organ damage.”

About the study

Over the past several years, unsuccessful attempts have been made to develop prediction models for patients with type 2 DM. More recently, a European Heart Journal study revealed the development of a new model called SCORE 2D that can predict the ten-year risk of CV disease in European individuals with type 2 DM. This model was created by the SCORE 2-Diabetes working group and the European Society of Cardiology (ESC) Cardiovascular Risk Collaboration.

SCORE 2D was developed by extending SCORE 2 algorithms based on data from four large-scale populations with type 2 DM free from CV disease. In addition to the already included risk factors of systolic blood pressure, smoking, age, and total and high-density lipid (HDL) cholesterol, three DM-specific variables were included. These variables were age at diabetes onset, estimated glomerular filtration rate, and glycated hemoglobin A1c (HbA1c). 

The current model was validated using four European cohorts from different regions that were considered to be at low, moderate, high, and very high risk of CV. As compared to the earlier models, SCORE 2D exhibited significant performance in providing preventive interventions for people with type 2 DM across Europe. 

Conclusions

Despite these positive results, the applicability and accuracy of SCORE 2D must be further assessed, as it is imperative to ascertain whether the added risk factors are adequate. For example, albuminuria, which is a known risk factor for CV disease incidence, has not been considered due to a lack of data availability.

Regardless of the aforementioned limitations associated with SCORE 2D, the use of this model could ultimately support clinicians in their diagnosis and treatment approaches.