SCORE2- diabetes prediction model estimates the 10 year risk of cardiovascular disease in individuals with type 2 diabetes

In a recent study published in the European Heart Journal, researchers described the development and validation process of SCORE2-Diabetes, a prediction model containing a recalibrated algorithm to predict the 10-year risk of cardiovascular disease in type-2 diabetes patients in Europe.

Study: SCORE2-Diabetes: 10-year cardiovascular risk estimation in type 2 diabetes in Europe. Image Credit: WITNGAOKAEW/Shutterstock.com

Background

Type-2 diabetes is one of the significant risk factors for cardiovascular disease, a prevalent cause of mortality worldwide. In high-income countries, type-2 diabetes is believed to double the risk of cardiovascular disease.

Many of the models for risk prediction estimate the 10-year risk of cardiovascular disease for an individual by considering the diabetes status along with conventional risk factors such as the levels of total and high-density lipoprotein cholesterol, smoking behavior, age, and systolic blood pressure.

Furthermore, many published risk assessment models have begun including diabetes-specific parameters such as glycated hemoglobin (HbA1c), kidney function markers, and the age of diabetes diagnosis in assessing cardiovascular disease risk.

However, because many of these risk predictors have been developed based on the results of interventional trials or observational studies, they have not been statistically adapted to account for the varying rates of cardiovascular disease across Europe.

About the study

In the present study, the researchers used individual data for participants registered in four data sources — the United Kingdom Biobank (UKB), Scottish Care Information—Diabetes (SCID), Emerging Risk Factors Collaboration (ERFC), and Clinical Practice Research Datalink (CPRD) — from England, Scotland, Wales, France, Italy, Germany, and the United States.

This data was used to adapt the original risk prediction model SCORE2 which assessed the risk of non-fatal and fatal cardiovascular disease.

The risk models were recalibrated for each European risk region and validated for type-2 diabetes patients in Croatia, Malta, Spain, and Sweden.

Additionally, the variation in cardiovascular disease risk between type-2 diabetes patients was determined using the recalibrated models to examine the contemporary populations in each of the European risk regions.

The data for the model derivation comprised information from individual participants above 40, diagnosed with type-2 diabetes but with no history of cardiovascular disease.

The data obtained from UKB, SCID, ERFC, and CPRD was restricted to England and included participants diagnosed with type-2 diabetes on June 1^st, 2008, and whose risk factors measurements were obtained between June 30^th, 2006, and December 31^st, 2008.

Additionally, follow-up data included records of non-fatal cardiovascular events between June 1^st and December 31^st, 2019.

During the validation of the risk prediction model, the primary outcome was cardiovascular disease events consisting of cardiovascular mortality, non-fatal stroke, and non-fatal myocardial infarction. At the same time, deaths due to non-cardiovascular reasons were considered competing events.

Results

The results indicated that the recalibrated SCORE2-Diabetes risk prediction model improved the identification of increased cardiovascular disease risk across the varied risk regions of Europe. The recalibration resulted in a three to four-times better estimation of cardiovascular disease for a set of risk factors.

Furthermore, since the model recalibration used registry data and was not dependent on the results of interventional or observational studies, it could be updated to determine the cardiovascular disease risk of any target population.

Therefore, the risk prediction model can be revised for any region of Europe that has epidemiological data specific for different ages and sexes.

Additionally, while the recalibrated SCORE2-Diabetes model can incorporate the population-level variation across the risk regions of Europe because it considers specific risk factors, including kidney function, HbA1c, and the age of diabetes diagnosis, it can also provide accurate risk predictions at an individual level.

Therefore, not only can it be used to estimate cardiovascular disease risk for larger populations, but it also has individual applications in helping clinicians and patients determine the type and intensity of the interventions to prevent cardiovascular disease.

Moreover, the external validation involving over 210,000 individuals from across varied risk regions highlighted the efficiency and generalizability of the model in predicting cardiovascular disease risk across a diverse population.

Conclusions

To summarize, the researchers recalibrated the existing SCORE2 prediction model to accurately predict the 10-year risk of first-onset cardiovascular disease in type-2 diabetes patients across the different risk regions in Europe.

The validation of SCORE2-Diabetes across four European countries from diverse risk regions indicated that the model could accurately predict the risk of cardiovascular disease associated with type-2 diabetes at individual and population levels.

Written by

Dr. Chinta Sidharthan

Chinta Sidharthan is a writer based in Bangalore, India. Her academic background is in evolutionary biology and genetics, and she has extensive experience in scientific research, teaching, science writing, and herpetology. Chinta holds a Ph.D. in evolutionary biology from the Indian Institute of Science and is passionate about science education, writing, animals, wildlife, and conservation. For her doctoral research, she explored the origins and diversification of blindsnakes in India, as a part of which she did extensive fieldwork in the jungles of southern India. She has received the Canadian Governor General’s bronze medal and Bangalore University gold medal for academic excellence and published her research in high-impact journals.