SCORE2 cardiovascular risk prediction models in an ethnic and socioeconomic diverse population in the Netherlands: an external validation study.

Cardiovascular disease Ethnicity Health disparities Risk factors Socioeconomic factors

Journal

EClinicalMedicine
ISSN: 2589-5370
Titre abrégé: EClinicalMedicine
Pays: England
ID NLM: 101733727

Informations de publication

Date de publication:
Mar 2023
Historique:
received: 17 11 2022
revised: 19 01 2023
accepted: 26 01 2023
entrez: 3 3 2023
pubmed: 4 3 2023
medline: 4 3 2023
Statut: epublish

Résumé

Socioeconomic status and ethnicity are not explicitly incorporated as risk factors in the four SCORE2 cardiovascular disease (CVD) risk models developed for country-wide implementation across Europe (low, moderate, high and very-high model). The aim of this study was to evaluate the performance of the four SCORE2 CVD risk prediction models in an ethnic and socioeconomic diverse population in the Netherlands. The SCORE2 CVD risk models were externally validated in socioeconomic and ethnic (by country of origin) subgroups, from a population-based cohort in the Netherlands, with GP, hospital and registry data. In total 155,000 individuals, between 40 and 70 years old in the study period from 2007 to 2020 and without previous CVD or diabetes were included. Variables (age, sex, smoking status, blood pressure, cholesterol) and outcome first CVD event (stroke, myocardial infarction, CVD death) were consistent with SCORE2. 6966 CVD events were observed, versus 5495 events predicted by the CVD low-risk model (intended for use in the Netherlands). Relative underprediction was similar in men and women (observed/predicted (OE-ratio), 1.3 and 1.2 in men and women, respectively). Underprediction was larger in low socioeconomic subgroups of the overall study population (OE-ratio 1.5 and 1.6 in men and women, respectively), and comparable in Dutch and the combined "other ethnicities" low socioeconomic subgroups. Underprediction in the Surinamese subgroup was largest (OE-ratio 1.9, in men and women), particularly in the low socioeconomic Surinamese subgroups (OE-ratio 2.5 and 2.1 in men and women). In the subgroups with underprediction in the low-risk model, the intermediate or high-risk SCORE2 models showed improved OE-ratios. Discrimination showed moderate performance in all subgroups and the four SCORE2 models, with C-statistics between 0.65 and 0.72, similar to the SCORE2 model development study. The SCORE 2 CVD risk model for low-risk countries (as the Netherlands are) was found to underpredict CVD risk, particularly in low socioeconomic and Surinamese ethnic subgroups. Including socioeconomic status and ethnicity as predictors in CVD risk models and implementing CVD risk adjustment within countries is desirable for adequate CVD risk prediction and counselling. Leiden University Medical Centre and Leiden University.

Sections du résumé

Background UNASSIGNED
Socioeconomic status and ethnicity are not explicitly incorporated as risk factors in the four SCORE2 cardiovascular disease (CVD) risk models developed for country-wide implementation across Europe (low, moderate, high and very-high model). The aim of this study was to evaluate the performance of the four SCORE2 CVD risk prediction models in an ethnic and socioeconomic diverse population in the Netherlands.
Methods UNASSIGNED
The SCORE2 CVD risk models were externally validated in socioeconomic and ethnic (by country of origin) subgroups, from a population-based cohort in the Netherlands, with GP, hospital and registry data. In total 155,000 individuals, between 40 and 70 years old in the study period from 2007 to 2020 and without previous CVD or diabetes were included. Variables (age, sex, smoking status, blood pressure, cholesterol) and outcome first CVD event (stroke, myocardial infarction, CVD death) were consistent with SCORE2.
Findings UNASSIGNED
6966 CVD events were observed, versus 5495 events predicted by the CVD low-risk model (intended for use in the Netherlands). Relative underprediction was similar in men and women (observed/predicted (OE-ratio), 1.3 and 1.2 in men and women, respectively). Underprediction was larger in low socioeconomic subgroups of the overall study population (OE-ratio 1.5 and 1.6 in men and women, respectively), and comparable in Dutch and the combined "other ethnicities" low socioeconomic subgroups. Underprediction in the Surinamese subgroup was largest (OE-ratio 1.9, in men and women), particularly in the low socioeconomic Surinamese subgroups (OE-ratio 2.5 and 2.1 in men and women). In the subgroups with underprediction in the low-risk model, the intermediate or high-risk SCORE2 models showed improved OE-ratios. Discrimination showed moderate performance in all subgroups and the four SCORE2 models, with C-statistics between 0.65 and 0.72, similar to the SCORE2 model development study.
Interpretation UNASSIGNED
The SCORE 2 CVD risk model for low-risk countries (as the Netherlands are) was found to underpredict CVD risk, particularly in low socioeconomic and Surinamese ethnic subgroups. Including socioeconomic status and ethnicity as predictors in CVD risk models and implementing CVD risk adjustment within countries is desirable for adequate CVD risk prediction and counselling.
Funding UNASSIGNED
Leiden University Medical Centre and Leiden University.

Identifiants

pubmed: 36864978
doi: 10.1016/j.eclinm.2023.101862
pii: S2589-5370(23)00039-1
pmc: PMC9971516
doi:

Types de publication

Journal Article

Langues

eng

Pagination

101862

Informations de copyright

© 2023 The Author(s).

Déclaration de conflit d'intérêts

All authors declare no competing interests.

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Auteurs

Janet M Kist (JM)

Health Campus The Hague, Leiden University Medical Centre, The Hague, The Netherlands.

Rimke C Vos (RC)

Health Campus The Hague, Leiden University Medical Centre, The Hague, The Netherlands.

Albert T A Mairuhu (ATA)

Department of Internal Medicine, HAGA Teaching Hospital, The Hague, The Netherlands.

Jeroen N Struijs (JN)

Health Campus The Hague, Leiden University Medical Centre, The Hague, The Netherlands.
National Institute for Public Health and the Environment, Bilthoven, The Netherlands.

Petra G van Peet (PG)

Health Campus The Hague, Leiden University Medical Centre, The Hague, The Netherlands.

Hedwig M M Vos (HMM)

Health Campus The Hague, Leiden University Medical Centre, The Hague, The Netherlands.

Hendrikus J A van Os (HJA)

Health Campus The Hague, Leiden University Medical Centre, The Hague, The Netherlands.
National eHealth Living Lab, Leiden University Medical Centre, Leiden, The Netherlands.

Edith D Beishuizen (ED)

Department of Internal Medicine, HMC Hospital, The Hague, The Netherlands.

Yvo W J Sijpkens (YWJ)

Department of Internal Medicine, HMC Hospital, The Hague, The Netherlands.

Mohammad A Faiq (MA)

Health Campus The Hague, Leiden University Medical Centre, The Hague, The Netherlands.

Mattijs E Numans (ME)

Health Campus The Hague, Leiden University Medical Centre, The Hague, The Netherlands.

Rolf H H Groenwold (RHH)

Department of Clinical Epidemiology, Leiden University Medical Centre, Leiden, The Netherlands.
Department of Biomedical Data Science, Leiden University Medical Centre, Leiden, The Netherlands.

Classifications MeSH