TY - JOUR
T1 - Biomarker-based prediction of fatal and non-fatal cardiovascular outcomes in individuals with diabetes mellitus
AU - Haller, Paul M
AU - Goßling, Alina
AU - Magnussen, Christina
AU - Brenner, Hermann
AU - Schöttker, Ben
AU - Iacoviello, Licia
AU - Costanzo, Simona
AU - Kee, Frank
AU - Koenig, Wolfgang
AU - Linneberg, Allan
AU - Sujana, Chaterina
AU - Thorand, Barbara
AU - Salomaa, Veikko
AU - Niiranen, Teemu J
AU - Söderberg, Stefan
AU - Völzke, Henry
AU - Dörr, Marcus
AU - Sans, Susana
AU - Padró, Teresa
AU - Felix, Stephan B
AU - Nauck, Matthias
AU - Petersmann, Astrid
AU - Palmieri, Luigi
AU - Donfrancesco, Chiara
AU - De Ponti, Roberto
AU - Veronesi, Giovanni
AU - Ferrario, Marco M
AU - Kuulasmaa, Kari
AU - Zeller, Tanja
AU - Ojeda, Francisco
AU - Blankenberg, Stefan
AU - Westermann, Dirk
AU - BiomarCaRE Consortium
N1 - © The Author(s) 2023. Published by Oxford University Press on behalf of the European Society of Cardiology. All rights reserved. For permissions, please e-mail: [email protected].
PY - 2023/9/6
Y1 - 2023/9/6
N2 - 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.
AB - 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.
KW - Biomarkers/metabolism
KW - C-Reactive Protein/metabolism
KW - Cardiovascular Diseases/epidemiology
KW - Diabetes Mellitus
KW - Humans
KW - Natriuretic Peptide, Brain
KW - Peptide Fragments
KW - Prognosis
KW - Risk Factors
UR - http://www.scopus.com/inward/record.url?scp=85169848670&partnerID=8YFLogxK
U2 - 10.1093/eurjpc/zwad122
DO - 10.1093/eurjpc/zwad122
M3 - Journal article
C2 - 37079290
SN - 2047-4873
VL - 30
SP - 1218
EP - 1226
JO - European Journal of Preventive Cardiology
JF - European Journal of Preventive Cardiology
IS - 12
ER -