Year: 2023
Type: article
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. 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. 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.
Source: European Heart Journal
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
Language: English
Subfield: Endocrinology, Diabetes and Metabolism
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $4,584
Funders: Abbott Laboratories, Amgen, Eli Lilly and Company, Pfizer, AstraZeneca, Bayer, GlaxoSmithKline, Sanofi, Gilead Sciences, Deutsches Krebsforschungszentrum, Queen Mary University of London, National University of Ireland, Regeneron Pharmaceuticals, Wellcome Trust, National Institute for Health and Care Excellence, Scottish Government, Ionis Pharmaceuticals, Mylan, Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, National Institute for Health and Care Research, British Heart Foundation, Department of Health and Social Care, Kidney Research UK, Research Councils UK, University of Cambridge, Imperial College London, University College London, University of Oxford, University of Glasgow, European Society of Cardiology, University of Bristol, Public Health Agency, University of Galway, Trinity College Dublin, Universität Heidelberg, Institut National de la Santé et de la Recherche Médicale, Universiteit Utrecht, Bundesministerium für Gesundheit, Novo Nordisk, Universiteit Gent, China Scholarship Council, Astellas Pharma, Österreichische Forschungsförderungsgesellschaft, BHF Centre of Research Excellence, Oxford, Technische Universität München, Sahlgrenska Universitetssjukhuset, Università di Bologna, Konung Gustaf V:s och Drottning Victorias Frimurarestiftelse, Univerza v Ljubljani, Debreceni Egyetem, Medizinische Universität Innsbruck, Universität Innsbruck, Centro de Investigación Biomédica en Red Diabetes y Enfermedades Metabólicas Asociadas, Institut Català de la Salut, Robert Koch Institut, Chief Scientist Office, Scottish Government Health and Social Care Directorate, Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Instituto de Salud Carlos III, Health and Social Care Research and Development Division, NIHR Cambridge Biomedical Research Centre, Daiichi Sankyo Europe, Health Data Research UK
Awards: G1050023690, G139696651, G1521853241, G1671907826, G1680483594, G1953244154, G2165920734, G2372829998, Large-scale integrative genomic studies of high-dimensional traits in cardiovascular diseases (renewal), G2493601830, G2537968379, G3217060148, NIHR Senior Investigator Award, Research Excellence (round 3), G356994587, G3584577881, G370598735, G3986547339, G4085921672, G4211044638, G428372581, G4584873075, G4753630297, G4761731823, G5314081182, G5367938058, G6058803565, G6077662935, G645047804, G6538311282, G6641991021, The BHF-Turing Cardiovascular Data Science Awards (First call): Using machine learning for personalised CVD risk management (joint funding with The Alan Turing Institute), Large-scale integrative studies of risk factors in coronary heart disease: from discovery to application (renewal). (Joint funding with MRC), G762219591, G763011351, G7826725679, G7939076303, Large-scale integrative studies of risk factors in coronary heart disease: from discovery to application
OpenAlex ID: W4378746292