| Title: | SCORE2-Diabetes: 10-year cardiovascular risk estimation in type 2 diabetes in Europe |
| Journal: | European Heart Journal |
| Published: | 29 May 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/37247330/ |
| DOI: | https://doi.org/10.1093/eurheartj/ehad260 |
| URL: | https://academic.oup.com/eurheartj/advance-article-pdf/doi/10.1093/eurheartj/ehad260/50482240/ehad260.pdf |
Publication 11504
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Abstract
AIMS: To develop and validate a recalibrated prediction model (SCORE2-Diabetes) to estimate the 10-year risk of cardiovascular disease (CVD) in individuals with type 2 diabetes in Europe.</p>
METHODS AND RESULTS: SCORE2-Diabetes was developed by extending SCORE2 algorithms using individual-participant data from four large-scale datasets comprising 229 460 participants (43 706 CVD events) with type 2 diabetes and without previous CVD. Sex-specific competing risk-adjusted models were used including conventional risk factors (i.e. age, smoking, systolic blood pressure, total, and HDL-cholesterol), as well as diabetes-related variables (i.e. age at diabetes diagnosis, glycated haemoglobin [HbA1c] and creatinine-based estimated glomerular filtration rate [eGFR]). Models were recalibrated to CVD incidence in four European risk regions. External validation included 217 036 further individuals (38 602 CVD events), and showed good discrimination, and improvement over SCORE2 (C-index change from 0.009 to 0.031). Regional calibration was satisfactory. SCORE2-Diabetes risk predictions varied several-fold, depending on individuals' levels of diabetes-related factors. For example, in the moderate-risk region, the estimated 10-year CVD risk was 11% for a 60-year-old man, non-smoker, with type 2 diabetes, average conventional risk factors, HbA1c of 50 mmol/mol, eGFR of 90 mL/min/1.73 m2, and age at diabetes diagnosis of 60 years. By contrast, the estimated risk was 17% in a similar man, with HbA1c of 70 mmol/mol, eGFR of 60 mL/min/1.73 m2, and age at diabetes diagnosis of 50 years. For a woman with the same characteristics, the risk was 8% and 13%, respectively.</p>
CONCLUSION: SCORE2-Diabetes, a new algorithm developed, calibrated, and validated to predict 10-year risk of CVD in individuals with type 2 diabetes, enhances identification of individuals at higher risk of developing CVD across Europe.</p>
99 Authors
- Lisa Pennells
- Stephen Kaptoge
- Helena Bleken Østergaard
- Stephanie H Read
- Fabrizio Carinci
- Josep Franch-Nadal
- Carmen Petitjean
- Owen Taylor
- Steven H J Hageman
- Zhe Xu
- Fanchao Shi
- Sarah Spackman
- Stefano Gualdi
- Naomi Holman
- Rui Bebiano Da Providencia E Costa
- Fabrice Bonnet
- Hermann Brenner
- Richard F Gillum
- Stefan Kiechl
- Deborah A Lawlor
- Louis Potier
- Ben Schöttker
- Reecha Sofat
- Henry Völzke
- Johann Willeit
- Zane Baltane
- Stephen Fava
- Sandor Janos
- Astrid Lavens
- Santa Pildava
- Tamara Poljicanin
- Ivan Pristas
- Peter Rossing
- Reiff Sascha
- Christa Scheidt-Nave
- Iztok Stotl
- Gail Tibor
- Vilma Urbančič-Rovan
- An-Sofie Vanherwegen
- Dorte Vistisen
- Yong Du
- Matthew R Walker
- Peter Willeit
- Brian Ference
- Dirk De Bacquer
- Martin Halle
- Radu Huculeci
- John William McEvoy
- Adam Timmis
- Panagiotis Vardas
- Jannick A N Dorresteijn
- Ian Graham
- Angela Wood
- Björn Eliasson
- William Herrington
- John Danesh
- Dídac Mauricio
- Massimo Massi Benedetti
- Naveed Sattar
- Frank L J Visseren
- Sarah Wild
- Emanuele Di Angelantonio
- Beverley Balkau
- Fabrice Bonnet
- Frederic Fumeron
- Hannah Stocker
- Bernd Holleczek
- Sabine Schipf
- Carsten Oliver Schmidt
- Marcus Dörr
- Herbert Tilg
- Christoph Leitner
- Marlene Notdurfter
- Julie Taylor
- Caroline Dale
- David Prieto-Merino
- Richard F Gillum
- Astrid Lavens
- An-Sofie Vanherwegen
- Tamara Poljicanin
- Ivan Pristas
- Tamara Buble
- Pero Ivanko
- Peter Rossing
- Bendix Carstensen
- Christin Heidemann
- Yong Du
- Christa Scheidt-Nave
- Tibor Gall
- Janos Sandor
- Zane Baltane
- Santa Pildava
- Jana Lepiksone
- Caroline J Magri
- Joseph Azzopardi
- Iztok Stotl
- Jordi Real
- Bogdan Vlacho
- Manel Mata-Cases
1 Application
| Application ID | Title |
|---|---|
| 13784 | Correlates and Consequences of Cardiometabolic multimorbidity |
Enabling scientific discoveries that improve human health