Estimating individual lifetime risk of incident cardiovascular events in adults with Type 2 diabetes: an update and geographical calibration of the DIAbetes Lifetime perspective model (DIAL2)

Author:

Østergaard Helena Bleken1,Hageman Steven H J1ORCID,Read Stephanie H23ORCID,Taylor Owen4,Pennells Lisa4ORCID,Kaptoge Stephen4ORCID,Petitjean Carmen4,Xu Zhe4ORCID,Shi Fanchao4,McEvoy John William5,Herrington William6ORCID,Visseren Frank L J1ORCID,Wood Angela4ORCID,Eliasson Björn7,Sattar Naveed8ORCID,Wild Sarah23ORCID,Di Angelantonio Emanuele49ORCID,Dorresteijn Jannick A N1ORCID

Affiliation:

1. Department of Vascular Medicine, University Medical Center Utrecht, Utrecht University , Heidelberglaan 100, 3584 CX Utrecht , the Netherlands

2. Usher Institute, University of Edinburgh , Craigour House, 450 Old Dalkeith Rd, Edinburgh EH16 4SS , UK

3. On behalf of the Scottish Diabetes Research Network epidemiology group , Diabetes Support Unit, Level 8, Ninewells Hospital, DundeeDD1 9SY , UK

4. Department of Public Health and Primary Care, University of Cambridge , Forvie Site, Robinson Way, Cambridge CB2 0SR , UK

5. National University of Ireland Galway , University Rd, Galway , Ireland

6. Medical Research Council Population Health Research Unit at the University of Oxford, Nuffield Department of Population Health, University of Oxford , Richard Doll Building, Old Road Campus, Headington, Oxford OX3 7LF , UK

7. Department of Molecular and Clinical Medicine, University of Gothenburg , Blå stråket 5 B Wallenberglab, SU41345 Göteborg , Sweden

8. Institute of Cardiovascular & Medical Sciences, University of Glasgow , 126 University Place, G12 8TA Glasgow , UK

9. Health Data Science Centre, Human Technopole , V.le Rita Levi-Montalcini, 1, 20157 Milano MI , Italy

Abstract

Abstract Aims The 2021 European Society of Cardiology cardiovascular disease (CVD) prevention guidelines recommend the use of (lifetime) risk prediction models to aid decisions regarding intensified preventive treatment options in adults with Type 2 diabetes, e.g. the DIAbetes Lifetime perspective model (DIAL model). The aim of this study was to update the DIAL model using contemporary and representative registry data (DIAL2) and to systematically calibrate the model for use in other European countries. Methods and results The DIAL2 model was derived in 467 856 people with Type 2 diabetes without a history of CVD from the Swedish National Diabetes Register, with a median follow-up of 7.3 years (interquartile range: 4.0–10.6 years) and comprising 63 824 CVD (including fatal CVD, non-fatal stroke and non-fatal myocardial infarction) events and 66 048 non-CVD mortality events. The model was systematically recalibrated to Europe’s low- and moderate-risk regions using contemporary incidence data and mean risk factor distributions. The recalibrated DIAL2 model was externally validated in 218 267 individuals with Type 2 diabetes from the Scottish Care Information—Diabetes (SCID) and Clinical Practice Research Datalink (CPRD). In these individuals, 43 074 CVD events and 27 115 non-CVD fatal events were observed. The DIAL2 model discriminated well, with C-indices of 0.732 [95% confidence interval (CI) 0.726–0.739] in CPRD and 0.700 (95% CI 0.691–0.709) in SCID. Conclusion The recalibrated DIAL2 model provides a useful tool for the prediction of CVD-free life expectancy and lifetime CVD risk for people with Type 2 diabetes without previous CVD in the European low- and moderate-risk regions. These long-term individualized measures of CVD risk are well suited for shared decision-making in clinical practice as recommended by the 2021 CVD ESC prevention guidelines.

Publisher

Oxford University Press (OUP)

Subject

Cardiology and Cardiovascular Medicine,Epidemiology

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