Sukainah A Alfaraj, Janet M Kist, Rolf H H Groenwold, Marco Spruit, Dennis Mook-Kanamori, Rimke C Vos
{"title":"External validation of SCORE2-Diabetes in the Netherlands across various Socioeconomic levels in native-Dutch and non-Dutch populations.","authors":"Sukainah A Alfaraj, Janet M Kist, Rolf H H Groenwold, Marco Spruit, Dennis Mook-Kanamori, Rimke C Vos","doi":"10.1093/eurjpc/zwae354","DOIUrl":null,"url":null,"abstract":"<p><strong>Aims: </strong>Adults with type 2 diabetes have an increased risk of cardiovascular events (CVE), the world's leading cause of mortality. The SCORE2-Diabetes model is a tool designed to estimate the 10-year risk of CVE specifically in individuals with type 2 diabetes. However, the performance of such models may vary across different demographic and socioeconomic groups, necessitating validation and assessment in diverse populations. This study aims to externally validate SCORE2-Diabetes and assess its performance across various socioeconomic and migration origins in the Netherlands.</p><p><strong>Methods: </strong>We selected adults with type 2 diabetes, aged 40-79 years and without previous CVE from the Extramural LUMC Academic Network (ELAN) primary care data cohort from 2007 to 2023. ELAN data were linked with Statistics Netherlands registry data to obtain information about the country of origin and socioeconomic status (SES). CVE was defined as myocardial infarction, stroke, or CV mortality. Non-CV mortality was considered a competing event. Analyses were stratified by sex, Dutch versus other non-Dutch countries of origin, and quintiles of SES.</p><p><strong>Results: </strong>Of the 26,544 included adults with type 2 diabetes, 2,518 developed CVE. SCORE2-Diabetes showed strong predictive accuracy for CVE in the Dutch population (observed-to-expected ratio (OE)=1.000, 95% CI=0.990-1.008 for men, and OE=1.050, 95% CI=1.042-1.057 for women). For non-Dutch individuals, the model underestimated CVE risk (OE=1.121, 95% CI=1.108-1.131 for men, and OE=1.100, 95% CI=1.092-1.111 for women). The model also underestimated the CVE risk (OE>1) in low SES groups and overestimated the risk (OE<1) in high SES groups. Discrimination was moderate across subgroups with c-indices between 0.6 and 0.7.</p><p><strong>Conclusions: </strong>SCORE2-Diabetes accurately predicted the risk of CVE in the Dutch population. However, it underpredicted the risk of CVE in the low SES groups and non-Dutch origins, while overpredicting the risk in high SES men and women. Additional clinical judgment must be considered when using SCORE2-Diabetes for different SES and countries of origin.</p>","PeriodicalId":12051,"journal":{"name":"European journal of preventive cardiology","volume":null,"pages":null},"PeriodicalIF":8.4000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"European journal of preventive cardiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/eurjpc/zwae354","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Aims: Adults with type 2 diabetes have an increased risk of cardiovascular events (CVE), the world's leading cause of mortality. The SCORE2-Diabetes model is a tool designed to estimate the 10-year risk of CVE specifically in individuals with type 2 diabetes. However, the performance of such models may vary across different demographic and socioeconomic groups, necessitating validation and assessment in diverse populations. This study aims to externally validate SCORE2-Diabetes and assess its performance across various socioeconomic and migration origins in the Netherlands.
Methods: We selected adults with type 2 diabetes, aged 40-79 years and without previous CVE from the Extramural LUMC Academic Network (ELAN) primary care data cohort from 2007 to 2023. ELAN data were linked with Statistics Netherlands registry data to obtain information about the country of origin and socioeconomic status (SES). CVE was defined as myocardial infarction, stroke, or CV mortality. Non-CV mortality was considered a competing event. Analyses were stratified by sex, Dutch versus other non-Dutch countries of origin, and quintiles of SES.
Results: Of the 26,544 included adults with type 2 diabetes, 2,518 developed CVE. SCORE2-Diabetes showed strong predictive accuracy for CVE in the Dutch population (observed-to-expected ratio (OE)=1.000, 95% CI=0.990-1.008 for men, and OE=1.050, 95% CI=1.042-1.057 for women). For non-Dutch individuals, the model underestimated CVE risk (OE=1.121, 95% CI=1.108-1.131 for men, and OE=1.100, 95% CI=1.092-1.111 for women). The model also underestimated the CVE risk (OE>1) in low SES groups and overestimated the risk (OE<1) in high SES groups. Discrimination was moderate across subgroups with c-indices between 0.6 and 0.7.
Conclusions: SCORE2-Diabetes accurately predicted the risk of CVE in the Dutch population. However, it underpredicted the risk of CVE in the low SES groups and non-Dutch origins, while overpredicting the risk in high SES men and women. Additional clinical judgment must be considered when using SCORE2-Diabetes for different SES and countries of origin.
期刊介绍:
European Journal of Preventive Cardiology (EJPC) is an official journal of the European Society of Cardiology (ESC) and the European Association of Preventive Cardiology (EAPC). The journal covers a wide range of scientific, clinical, and public health disciplines related to cardiovascular disease prevention, risk factor management, cardiovascular rehabilitation, population science and public health, and exercise physiology. The categories covered by the journal include classical risk factors and treatment, lifestyle risk factors, non-modifiable cardiovascular risk factors, cardiovascular conditions, concomitant pathological conditions, sport cardiology, diagnostic tests, care settings, epidemiology, pharmacology and pharmacotherapy, machine learning, and artificial intelligence.