% IMPORTANT: The following is UTF-8 encoded. This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.
@ARTICLE{Haller:276226,
author = {P. M. Haller and A. Goßling and C. Magnussen and H.
Brenner$^*$ and B. Schöttker$^*$ and L. Iacoviello and S.
Costanzo and F. Kee and W. Koenig and A. Linneberg and C.
Sujana and B. Thorand and V. Salomaa and T. J. Niiranen and
S. Söderberg and H. Völzke and M. Dörr and S. Sans and T.
Padró and S. B. Felix and M. Nauck and A. Petersmann and L.
Palmieri and C. Donfrancesco and R. De Ponti and G. Veronesi
and M. M. Ferrario and K. Kuulasmaa and T. Zeller and F.
Ojeda and S. Blankenberg and D. Westermann},
collaboration = {B. Consortium},
title = {{B}iomarker-based prediction of fatal and non-fatal
cardiovascular outcomes in individuals with diabetes
mellitus.},
journal = {European journal of preventive cardiology},
volume = {30},
number = {12},
issn = {2047-4873},
address = {Oxford},
publisher = {Oxford University Press},
reportid = {DKFZ-2023-01035},
pages = {1218-1226},
year = {2023},
note = {2023 Sep 6;30(12):1218-1226},
abstract = {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.We used individual-level data of 95,292
individuals of the European population harmonized in the
BiomarCaRE 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 (adj-HR) 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, 6,090 $(6.4\%)$
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).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.},
keywords = {NT-proBNP (Other) / biomarkers (Other) / cardiovascular
events (Other) / diabetes (Other) / hs-CRP (Other) / hs-cTnI
(Other)},
cin = {C070},
ddc = {610},
cid = {I:(DE-He78)C070-20160331},
pnm = {313 - Krebsrisikofaktoren und Prävention (POF4-313)},
pid = {G:(DE-HGF)POF4-313},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:37079290},
doi = {10.1093/eurjpc/zwad122},
url = {https://inrepo02.dkfz.de/record/276226},
}