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| 001 | 276226 | ||
| 005 | 20240229154958.0 | ||
| 024 | 7 | _ | |a 10.1093/eurjpc/zwad122 |2 doi |
| 024 | 7 | _ | |a pmid:37079290 |2 pmid |
| 024 | 7 | _ | |a 2047-4873 |2 ISSN |
| 024 | 7 | _ | |a 2047-4881 |2 ISSN |
| 024 | 7 | _ | |a altmetric:148233746 |2 altmetric |
| 037 | _ | _ | |a DKFZ-2023-01035 |
| 041 | _ | _ | |a English |
| 082 | _ | _ | |a 610 |
| 100 | 1 | _ | |a Haller, Paul M |0 0000-0002-7714-4446 |b 0 |
| 245 | _ | _ | |a Biomarker-based prediction of fatal and non-fatal cardiovascular outcomes in individuals with diabetes mellitus. |
| 260 | _ | _ | |a Oxford |c 2023 |b Oxford University Press |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1694087367_25272 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 500 | _ | _ | |a 2023 Sep 6;30(12):1218-1226 |
| 520 | _ | _ | |a 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. |
| 536 | _ | _ | |a 313 - Krebsrisikofaktoren und Prävention (POF4-313) |0 G:(DE-HGF)POF4-313 |c POF4-313 |f POF IV |x 0 |
| 588 | _ | _ | |a Dataset connected to CrossRef, PubMed, , Journals: inrepo02.dkfz.de |
| 650 | _ | 7 | |a NT-proBNP |2 Other |
| 650 | _ | 7 | |a biomarkers |2 Other |
| 650 | _ | 7 | |a cardiovascular events |2 Other |
| 650 | _ | 7 | |a diabetes |2 Other |
| 650 | _ | 7 | |a hs-CRP |2 Other |
| 650 | _ | 7 | |a hs-cTnI |2 Other |
| 700 | 1 | _ | |a Goßling, Alina |0 0000-0002-5211-5593 |b 1 |
| 700 | 1 | _ | |a Magnussen, Christina |0 0000-0002-5102-0955 |b 2 |
| 700 | 1 | _ | |a Brenner, Hermann |0 P:(DE-He78)90d5535ff896e70eed81f4a4f6f22ae2 |b 3 |u dkfz |
| 700 | 1 | _ | |a Schöttker, Ben |0 P:(DE-He78)c67a12496b8aac150c0eef888d808d46 |b 4 |u dkfz |
| 700 | 1 | _ | |a Iacoviello, Licia |0 0000-0003-0514-5885 |b 5 |
| 700 | 1 | _ | |a Costanzo, Simona |0 0000-0003-4569-1186 |b 6 |
| 700 | 1 | _ | |a Kee, Frank |b 7 |
| 700 | 1 | _ | |a Koenig, Wolfgang |0 0000-0002-2064-9603 |b 8 |
| 700 | 1 | _ | |a Linneberg, Allan |0 0000-0002-0994-0184 |b 9 |
| 700 | 1 | _ | |a Sujana, Chaterina |b 10 |
| 700 | 1 | _ | |a Thorand, Barbara |0 0000-0002-5667-6849 |b 11 |
| 700 | 1 | _ | |a Salomaa, Veikko |0 0000-0001-7563-5324 |b 12 |
| 700 | 1 | _ | |a Niiranen, Teemu J |b 13 |
| 700 | 1 | _ | |a Söderberg, Stefan |b 14 |
| 700 | 1 | _ | |a Völzke, Henry |b 15 |
| 700 | 1 | _ | |a Dörr, Marcus |0 0000-0001-7471-475X |b 16 |
| 700 | 1 | _ | |a Sans, Susana |0 0000-0002-0400-5197 |b 17 |
| 700 | 1 | _ | |a Padró, Teresa |b 18 |
| 700 | 1 | _ | |a Felix, Stephan B |b 19 |
| 700 | 1 | _ | |a Nauck, Matthias |b 20 |
| 700 | 1 | _ | |a Petersmann, Astrid |b 21 |
| 700 | 1 | _ | |a Palmieri, Luigi |b 22 |
| 700 | 1 | _ | |a Donfrancesco, Chiara |0 0000-0002-8040-5571 |b 23 |
| 700 | 1 | _ | |a De Ponti, Roberto |b 24 |
| 700 | 1 | _ | |a Veronesi, Giovanni |0 0000-0002-4119-6615 |b 25 |
| 700 | 1 | _ | |a Ferrario, Marco M |b 26 |
| 700 | 1 | _ | |a Kuulasmaa, Kari |0 0000-0003-2165-1411 |b 27 |
| 700 | 1 | _ | |a Zeller, Tanja |b 28 |
| 700 | 1 | _ | |a Ojeda, Francisco |b 29 |
| 700 | 1 | _ | |a Blankenberg, Stefan |b 30 |
| 700 | 1 | _ | |a Westermann, Dirk |0 0000-0002-7542-1956 |b 31 |
| 700 | 1 | _ | |a Consortium, BiomarCaRE |b 32 |e Collaboration Author |
| 773 | _ | _ | |a 10.1093/eurjpc/zwad122 |g p. zwad122 |0 PERI:(DE-600)2646239-4 |n 12 |p 1218-1226 |t European journal of preventive cardiology |v 30 |y 2023 |x 2047-4873 |
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