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Article: Comparison of prediction models for cardiovascular and mortality risk in people with type 2 diabetes: An external validation in 23 685 adults included in the UK Biobank

TitleComparison of prediction models for cardiovascular and mortality risk in people with type 2 diabetes: An external validation in 23 685 adults included in the UK Biobank
Authors
Keywordscardiovascular
diabetes
prediction
risk
validation
Issue Date31-Jan-2024
PublisherWiley
Citation
Diabetes, Obesity and Metabolism, 2024 How to Cite?
Abstract

Aims

To validate cardiovascular risk prediction models for individuals with diabetes using the UK Biobank in order to assess their applicability.

Methods

We externally validated 19 cardiovascular risk scores from seven risk prediction models (Chang et al., Framingham, University of Hong Kong-Singapore [HKU-SG], Li et al, RECODe [risk equations for complications of type 2 diabetes], SCORE [Systematic Coronary Risk Evaluation] and the UK Prospective Diabetes Study Outcomes Model 2 [UKPDS OM2]), identified from systematic reviews, using UK Biobank data from 2006 to 2021 (n = 23 685; participant age 40–71 years, 63.5% male). We evaluated performance by assessing the discrimination and calibration of the models for the endpoints of mortality, cardiovascular mortality, congestive heart failure, myocardial infarction, stroke, and ischaemic heart disease.

Results

Over a total of 269 430 person-years of follow-up (median 11.89 years), the models showed low-to-moderate discrimination performance on external validation (concordance indices [c-indices] 0.50–0.71). Most models had low calibration with overprediction of the observed risk. RECODe outperformed other models across four comparable endpoints for discrimination: all-cause mortality (c-index 0.67, 95% confidence interval [CI] 0.65–0.69), congestive heart failure (c-index 0.71, 95% CI 0.69–0.72), myocardial infarction (c-index 0.67, 95% CI 0.65–0.68); and stroke (c-index 0.65, 95% CI 0.62–0.68), and for calibration (except for all-cause mortality). The UKPDS OM2 had comparable performance to RECODe for all-cause mortality (c-index 0.67, 95% CI 0.66–0.69) and cardiovascular mortality (c-index 0.71, 95% CI 0.70–0.73), but worse performance for other outcomes. The models performed better for younger participants and somewhat better for non-White ethnicities. Models developed from non-Western datasets showed worse performance in our UK-based validation set.

Conclusions

The RECODe model led to better risk estimations in this predominantly White European population. Further validation is needed in non-Western populations to assess generalizability to other populations.


Persistent Identifierhttp://hdl.handle.net/10722/339906
ISSN
2023 Impact Factor: 5.4
2023 SCImago Journal Rankings: 2.079
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorZhang, Yikun-
dc.contributor.authorOng Xin Jiong-
dc.contributor.authorTang, Shiqi-
dc.contributor.authorTang, Yui Chit-
dc.contributor.authorWong, Cheuk Tung-
dc.contributor.authorNg, Carmen S-
dc.contributor.authorQuan, Jianchao-
dc.date.accessioned2024-03-11T10:40:13Z-
dc.date.available2024-03-11T10:40:13Z-
dc.date.issued2024-01-31-
dc.identifier.citationDiabetes, Obesity and Metabolism, 2024-
dc.identifier.issn1462-8902-
dc.identifier.urihttp://hdl.handle.net/10722/339906-
dc.description.abstract<h3>Aims</h3><p>To validate cardiovascular risk prediction models for individuals with diabetes using the UK Biobank in order to assess their applicability.</p><h3>Methods</h3><p>We externally validated 19 cardiovascular risk scores from seven risk prediction models (Chang et al., Framingham, University of Hong Kong-Singapore [HKU-SG], Li et al, RECODe [risk equations for complications of type 2 diabetes], SCORE [Systematic Coronary Risk Evaluation] and the UK Prospective Diabetes Study Outcomes Model 2 [UKPDS OM2]), identified from systematic reviews, using UK Biobank data from 2006 to 2021 (<em>n</em> = 23 685; participant age 40–71 years, 63.5% male). We evaluated performance by assessing the discrimination and calibration of the models for the endpoints of mortality, cardiovascular mortality, congestive heart failure, myocardial infarction, stroke, and ischaemic heart disease.</p><h3>Results</h3><p>Over a total of 269 430 person-years of follow-up (median 11.89 years), the models showed low-to-moderate discrimination performance on external validation (concordance indices [c-indices] 0.50–0.71). Most models had low calibration with overprediction of the observed risk. RECODe outperformed other models across four comparable endpoints for discrimination: all-cause mortality (c-index 0.67, 95% confidence interval [CI] 0.65–0.69), congestive heart failure (c-index 0.71, 95% CI 0.69–0.72), myocardial infarction (c-index 0.67, 95% CI 0.65–0.68); and stroke (c-index 0.65, 95% CI 0.62–0.68), and for calibration (except for all-cause mortality). The UKPDS OM2 had comparable performance to RECODe for all-cause mortality (c-index 0.67, 95% CI 0.66–0.69) and cardiovascular mortality (c-index 0.71, 95% CI 0.70–0.73), but worse performance for other outcomes. The models performed better for younger participants and somewhat better for non-White ethnicities. Models developed from non-Western datasets showed worse performance in our UK-based validation set.</p><h3>Conclusions</h3><p>The RECODe model led to better risk estimations in this predominantly White European population. Further validation is needed in non-Western populations to assess generalizability to other populations.</p>-
dc.languageeng-
dc.publisherWiley-
dc.relation.ispartofDiabetes, Obesity and Metabolism-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectcardiovascular-
dc.subjectdiabetes-
dc.subjectprediction-
dc.subjectrisk-
dc.subjectvalidation-
dc.titleComparison of prediction models for cardiovascular and mortality risk in people with type 2 diabetes: An external validation in 23 685 adults included in the UK Biobank-
dc.typeArticle-
dc.identifier.doi10.1111/dom.15474-
dc.identifier.scopuseid_2-s2.0-85184206134-
dc.identifier.eissn1463-1326-
dc.identifier.isiWOS:001155420000001-
dc.identifier.issnl1462-8902-

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