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

Lay Summary In this work, the role of cardiac biomarkers measured from blood to predict cardiovascular events and death is tested in individuals of the general population and particularly in those with known diabetes. The work is based on a cooperation of different population studies across Europe and includes more than 90 000 individuals, with more than 6000 having diabetes. We could demonstrate that the determination of three cardiac biomarkers helps to identify individuals at highest risk for cardiovascular events (e.g. myocardial infarction or stroke) and death, despite accounting for known cardiovascular risk factors in these individuals. Therefore, these biomarkers should be considered for routine risk assessment for cardiovascular diseases and could improve the early identification of high-risk individuals, consequently leading to an earlier initiation of preventive therapies. 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.