Biomarker-based prediction of fatal and non-fatal cardiovascular outcomes in individuals with diabetes mellitus-Reference-Cited by-同舟云学术

Biomarker-based prediction of fatal and non-fatal cardiovascular outcomes in individuals with diabetes mellitus

Published:2023-04-20 Issue:12 Volume:30 Page:1218-1226
ISSN:2047-4873
Container-title:European Journal of Preventive Cardiology
language:en
Short-container-title:

Author:

Haller Paul M¹²^ORCID,Goßling Alina¹^ORCID,Magnussen Christina¹²^ORCID,Brenner Hermann³,Schöttker Ben³^ORCID,Iacoviello Licia⁴⁵^ORCID,Costanzo Simona⁴^ORCID,Kee Frank⁶,Koenig Wolfgang⁷⁸⁹^ORCID,Linneberg Allan¹⁰¹¹^ORCID,Sujana Chaterina¹²,Thorand Barbara¹²¹³^ORCID,Salomaa Veikko¹⁴^ORCID,Niiranen Teemu J¹⁴¹⁵,Söderberg Stefan¹⁶,Völzke Henry¹⁷¹⁸,Dörr Marcus¹⁸¹⁹^ORCID,Sans Susana²⁰^ORCID,Padró Teresa²¹,Felix Stephan B¹⁸¹⁹,Nauck Matthias¹⁸²²,Petersmann Astrid²²²³,Palmieri Luigi²⁴,Donfrancesco Chiara²⁴^ORCID,De Ponti Roberto⁵,Veronesi Giovanni⁵^ORCID,Ferrario Marco M⁵,Kuulasmaa Kari¹⁴^ORCID,Zeller Tanja¹²,Ojeda Francisco M¹,Blankenberg Stefan¹²,Westermann Dirk²⁵^ORCID,

Affiliation:

1. Department for Cardiology, University Heart and Vascular Center Hamburg, University Medical Center Hamburg-Eppendorf , Martinistrasse 52, 20246 Hamburg , Germany

2. German Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Kiel/Luebeck , Martinistrasse 52, 20246 Hamburg , Germany

3. German Cancer Research Center, Division of Clinical Epidemiology and Aging Research , Im Neuenheimer Feld 280, 69120 Heidelberg , Germany

4. 1) Department of Epidemiology and Prevention, IRCCS NEUROMED , Via Atinense, 18, 86077 Pozzilli , Italy

5. Research Center in Epidemiology and Preventive Medicine (EPIMED), Department of Medicine and Surgery, University of Insubria , Via O. Rossi 9, 21100 Varese , Italy

6. Centre for Public Health, Queens University of Belfast , Belfast BT12 6BA , UK

7. Klinik für Herz-& Kreislauferkrankungen, Deutsches Herzzentrum München, Technische Universität München , Lazarettstraße 36, 80636 München , Germany

8. German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance , Lazarettstraße 36, 80636 Munich , Germany

9. Institute of Epidemiology and Medical Biometry, University of Ulm , Helmholtzstr. 22, 89081 Ulm , Germany

10. Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, The Capital Region of Denmark , Ndr. Fasanvej 57, 1. sal, Bygning 14, 2000 Frederiksber , Denmark

11. Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen , Blegdamsvej 3B, 2200 Copenhagen , Denmark

12. Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Institute of Epidemiology , Ingolstädter Landstraße 1, 85764 Neuherberg , Germany

13. German Center for Diabetes Research (DZD) , Ingolstädter Landstraße 1, 85764 Neuherberg , Germany

14. Finnish Institute for Health and Welfare, Department of Public Health and Welfare , P.O. Box 30, FI-00271 Helsinki , Finland

15. Department of Medicine, Turku University Hospital and University of Turku , Kiinamyllynkatu 10, 20520 Turku , Finland

16. Department of Public Health and Clinical Medicine, Umeå University , 901 87 Umeå , Sweden

17. Institut für Community Medicine, Funktionsbereich SHIP/KEF, University Medicine Greifswald , Walter Rathenau Str. 48, 17475 Greifswald , Germany

18. German Center for Cardiovascular Research (DZHK), Partner Site Greifswald , Walter Rathenau Str. 48, 17475 Greifswald , Germany

19. Klinik und Poliklinik für Innere Medizin B, University Medicine Greifswald , Ferdinand-Sauerbruch-Straße, 17475 Greifswald , Germany

20. Catalan Department of Health , Roc Boronat, 81, 08005 Barcelona , Spain

21. Cardiovascular-Program ICCC, Institut d’Investigació Biomèdica Sant Pau (IIB SANT PAU) , Barcelona , Spain

22. Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald , Ferdinand-Sauerbruch-Straße, 17489 Greifswald , Germany

23. University Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Oldenburg , Rahel-Straus-Straße 10, 26133 Oldenburg , Germany

24. Department of Cardiovascular, Endocrine-metabolic Diseases and Aging, Istituto Superiore di Sanità-ISS , 299 Viale Regina Elena, 00161 Rome , Italy

25. Department of Cardiology and Angiology, University Heart Center Freiburg • Bad Krozingen , Breisacher Straße 153, 79110 Freiburg , Germany

Abstract

Abstract Aims The role of biomarkers in predicting cardiovascular outcomes in high-risk individuals is not well established. We aimed to investigate benefits of adding biomarkers to cardiovascular risk assessment in individuals with and without diabetes. Methods and results We used individual-level data of 95 292 individuals of the European population harmonized in the Biomarker for Cardiovascular Risk Assessment across Europe consortium and investigated the prognostic ability of high-sensitivity cardiac troponin I (hs-cTnI), N-terminal prohormone of brain natriuretic peptide (NT-proBNP), and high-sensitivity C-reactive protein (hs-CRP). Cox-regression models were used to determine adjusted hazard ratios of diabetes and log-transformed biomarkers for fatal and non-fatal cardiovascular events. Models were compared using the likelihood ratio test. Stratification by specific biomarker cut-offs was performed for crude time-to-event analysis using Kaplan–Meier plots. Overall, 6090 (6.4%) individuals had diabetes at baseline, median follow-up was 9.9 years. Adjusting for classical risk factors and biomarkers, diabetes [HR 2.11 (95% CI 1.92, 2.32)], and all biomarkers (HR per interquartile range hs-cTnI 1.08 [95% CI 1.04, 1.12]; NT-proBNP 1.44 [95% CI 1.37, 1.53]; hs-CRP 1.27 [95% CI 1.21, 1.33]) were independently associated with cardiovascular events. Specific cut-offs for each biomarker identified a high-risk group of individuals with diabetes losing a median of 15.5 years of life compared to diabetics without elevated biomarkers. Addition of biomarkers to the Cox-model significantly improved the prediction of outcomes (likelihood ratio test for nested models P < 0.001), accompanied by an increase in the c-index (increase to 0.81). Conclusion Biomarkers improve cardiovascular risk prediction in individuals with and without diabetes and facilitate the identification of individuals with diabetes at highest risk for cardiovascular events.

Funder

MORGAM

GenomEUtwin

ENGAGE

CHANCES

BiomarCaRE

euCanSHare

AFFECT-EU

Medical Research Council

Community Medicine Research Network of the University Medicine Greifswald

German Federal State of Mecklenburg

Health Administration of the Lombardia Region