Clin Res Cardiol (2021)
DOI DOI https://doi.org/10.1007/s00392-021-01843-w
Biomarker-associated cardiovascular risk in individuals with diabetes mellitus in the general population
P. Haller1, N. Makarova1, A. Goßling1, H. Brenner2, L. Iacoviello3, F. Kee4, W. Koenig5, A. Linneberg6, B. Thorand7, V. Salomaa8, S. Söderberg9, H. Völzke10, M. Dörr11, S. B. Felix11, M. Nauck12, K. Kuulasmaa8, T. Zeller1, S. Blankenberg1, D. Westermann1, für die Studiengruppe: BiomarCaRE
1Klinik für Kardiologie, Universitäres Herz- und Gefäßzentrum Hamburg GmbH, Hamburg; 2German Cancer Research Center, Heidelberg; 3Research Center in Epidemiology and Preventive Medicine (EPIMED). Department of Medicine and Surgery, Varese, IT; 4Centre for Public Health, Queens University of Belfast,, Belfast, UK; 5Klinik für Herz- und Kreislauferkrankungen, Deutsches Herzzentrum München, München; 6Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, The Capital Region of Denmark, Frederiksberg, DK; 7German Research Center for Environmental Heath (GmbH), Helmholtz Zentrum München, Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Neuherberg; 8Finnish Institute for Health and Welfare, Helsinki, FI; 9Department of Public Health and Clinical Medicine, Umeå, SE; 10Institut für Community Medicine, Funktionsbereich SHIP/KEF, Greifswald; 11Klinik und Poliklinik für Innere Medizin B, Universitätsmedizin Greifswald, Greifswald; 12Institut für klinische Chemie u. Laboratoriumsmedizin, Universitätsmedizin Greifswald, Greifswald;

Introduction: Biomarkers may reflect different aspects of coronary artery disease (CAD), including myocardial tissue damage (high-sensitive cardiac troponin [hs-cTn]) and hemodynamic stress (n-terminal prohormone of brain natriuretic peptide [NT-proBNP)), or represent a surrogate for its pathophysiology, i.e. inflammation (high-sensitivity c-reactive protein [hsCRP]).

Purpose: We determined the residual risk in patients with diabetes mellitus (DM), a high-risk group for cardiovascular complications, after accounting for these biomarkers.

Methods: Harmonized data of population-based studies from the biomarkers for cardiovascular risk assessment in Europe (BiomarCaRE) and MONIKA risk, genetics, archiving and monograph (MORGAM) consortia were used to calculate hazard ratios (HRa, 95% confidence intervals [CI]) for these biomarkers comparing patients with and without DM for their association with all-cause and cardiovascular (CV) death, CV disease and coronary revascularization during a median follow-up period of 9.6 years (maximum 28 years).

Results: We included 80,799 individuals, of whom 5,828 had DM (7.2%). Hs-cTnI, hsCRP and NT-proBNP were significantly higher in patients with DM(p<0.001, respectively). Cox-regression analysis revealed DM to be an independent predictor of all investigated outcomes, despite adjustment for clinical characteristics and the three biomarkers: all-cause death (adjHR 1.7 (95%ci 1.5, 1.9) p<0.001), CV death (adjHR 2.2 (95%ci 1.8, 2.6), p<0.001), CV disease (adjHR 2.2 (95%ci 2.0, 2.6), p<0.001) and coronary revascularization (adjHR 2.1 (95%ci 1.8, 2.5) p<0.001). Vice-versa, all biomarkers were independent predictors themselves (p<0.001, respectively). The adjHR for all-cause death according to biomarker concentrations for patients with and without DM are provided in Figure 1a-c. Regarding the ability to predict coronary revascularization, hsCRP behaved differently in patients with DM (adjHR 1.15 [95%ci 1.01; 1.31]) than in those without (adjHR 1.38 [95%ci 1.31; 1.45]; p-values for interaction = 0.0092). No interactions were observed for the other two biomarkers.  

Conclusion: Our findings confirm that risk prediction models including biomarkers perform differently in populations with DM. Differences in the ability of biomarkers, i.e hsCRP, to predict specific outcomes between patients with and without DM should be accounted for in future risk models.
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