Schiborn, C.* ; Kuhn, T.* ; Mühlenbruch, K.* ; Kuxhaus, O.* ; Weikert, C.* ; Fritsche, A. ; Kaaks, R.* ; Schulze, M.B.*
A newly developed and externally validated non-clinical score accurately predicts 10-year cardiovascular disease risk in the general adult population.
Sci. Rep. 11:19609 (2021)
Inclusion of clinical parameters limits the application of most cardiovascular disease (CVD) prediction models to clinical settings. We developed and externally validated a non-clinical CVD risk score with a clinical extension and compared the performance to established CVD risk scores. We derived the scores predicting CVD (non-fatal and fatal myocardial infarction and stroke) in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort (n = 25,992, cases = 683) using competing risk models and externally validated in EPIC-Heidelberg (n = 23,529, cases = 692). Performance was assessed by C-indices, calibration plots, and expected-to-observed ratios and compared to a non-clinical model, the Pooled Cohort Equation, Framingham CVD Risk Scores (FRS), PROCAM scores, and the Systematic Coronary Risk Evaluation (SCORE). Our non-clinical score included age, gender, waist circumference, smoking, hypertension, type 2 diabetes, CVD family history, and dietary parameters. C-indices consistently indicated good discrimination (EPIC-Potsdam 0.786, EPIC-Heidelberg 0.762) comparable to established clinical scores (thereof highest, FRS: EPIC-Potsdam 0.781, EPIC-Heidelberg 0.764). Additional clinical parameters slightly improved discrimination (EPIC-Potsdam 0.796, EPIC-Heidelberg 0.769). Calibration plots indicated very good calibration with minor overestimation in the highest decile of predicted risk. The developed non-clinical 10-year CVD risk score shows comparable discrimination to established clinical scores, allowing assessment of individual CVD risk in physician-independent settings.
Impact Factor
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Times Cited
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Publikationstyp
Artikel: Journalartikel
Dokumenttyp
Wissenschaftlicher Artikel
Typ der Hochschulschrift
Herausgeber
Schlagwörter
Multiple Imputation; Epic-germany; Follow-up; Model; Subdistribution; Association; Stroke; Tool
Keywords plus
Sprache
englisch
Veröffentlichungsjahr
2021
Prepublished im Jahr
HGF-Berichtsjahr
2021
ISSN (print) / ISBN
2045-2322
e-ISSN
2045-2322
ISBN
Bandtitel
Konferenztitel
Konferzenzdatum
Konferenzort
Konferenzband
Quellenangaben
Band: 11,
Heft: 1,
Seiten: ,
Artikelnummer: 19609
Supplement: ,
Reihe
Verlag
Nature Publishing Group
Verlagsort
London
Tag d. mündl. Prüfung
0000-00-00
Betreuer
Gutachter
Prüfer
Topic
Hochschule
Hochschulort
Fakultät
Veröffentlichungsdatum
0000-00-00
Anmeldedatum
0000-00-00
Anmelder/Inhaber
weitere Inhaber
Anmeldeland
Priorität
Begutachtungsstatus
Peer reviewed
POF Topic(s)
90000 - German Center for Diabetes Research
Forschungsfeld(er)
Helmholtz Diabetes Center
PSP-Element(e)
G-502400-001
Förderungen
German Cancer Research Center (DKFZ)
Federal Ministry of Science, Germany
European Union
German Cancer Aid
German Federal Ministry of Education and Research
German Federal Ministry of Education and Research through the German Center for Diabetes Research
State of Brandenburg through the German Center for Diabetes Research
Projekt DEAL
Copyright
Erfassungsdatum
2021-11-22