Nima Ghasemzedah1, Salim S Hayek1, Yi-An Ko1, Danny J Eapen1, Riyaz S Patel1, Pankaj Manocha1, Hatem Al Kassem1, Mohamed Khayata1, Emir Veledar1, Dimitrios Kremastinos1, Christian W Thorball1, Tomasz Pielak1, Sergey Sikora1, A Maziar Zafari1, Stamatios Lerakis1, Laurence Sperling1, Viola Vaccarino1, Stephen E Epstein1, Arshed A Quyyumi2. 1. From the Department of Medicine, Division of Cardiology, Emory University School of Medicine, Atlanta, GA (N.G., S.S.H., D.J.E., R.S.P., P.M., H.A.K., M.K., E.V., A.M.Z., S.L., L.S., V.V., A.A.Q.); Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA (Y.-A.K.); Institute of Cardiovascular Science, University College London, United Kingdom (R.S.P.); Division of Cardiology, Atlanta VA Medical Center, GA (A.M.Z.); Department of Biostatistics, Florida International University, Miami (E.V.); Department of Cardiology, University of Athens School of Medicine, Greece (D.K.); Clinical Research Centre, Copenhagen University Hospital, Denmark (C.W.T., T.P.); Stemedica Cell Technologies, Inc., San Diego, CA (S.S.); Department of Epidemiology, Emory University, Atlanta, GA (V.V.); and MedStar Heart and Vascular Institute, MedStar Washington Hospital Center, Washington, DC (S.E.E.). 2. From the Department of Medicine, Division of Cardiology, Emory University School of Medicine, Atlanta, GA (N.G., S.S.H., D.J.E., R.S.P., P.M., H.A.K., M.K., E.V., A.M.Z., S.L., L.S., V.V., A.A.Q.); Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA (Y.-A.K.); Institute of Cardiovascular Science, University College London, United Kingdom (R.S.P.); Division of Cardiology, Atlanta VA Medical Center, GA (A.M.Z.); Department of Biostatistics, Florida International University, Miami (E.V.); Department of Cardiology, University of Athens School of Medicine, Greece (D.K.); Clinical Research Centre, Copenhagen University Hospital, Denmark (C.W.T., T.P.); Stemedica Cell Technologies, Inc., San Diego, CA (S.S.); Department of Epidemiology, Emory University, Atlanta, GA (V.V.); and MedStar Heart and Vascular Institute, MedStar Washington Hospital Center, Washington, DC (S.E.E.). aquyyum@emory.edu.
Abstract
BACKGROUND: Inflammation, coagulation, and cell stress contribute to atherosclerosis and its adverse events. A biomarker risk score (BRS) based on the circulating levels of biomarkers C-reactive protein, fibrin degradation products, and heat shock protein-70 representing these 3 pathways was a strong predictor of future outcomes. We investigated whether soluble urokinase plasminogen activator receptor (suPAR), a marker of immune activation, is predictive of outcomes independent of the aforementioned markers and whether its addition to a 3-BRS improves risk reclassification. METHODS AND RESULTS: C-reactive protein, fibrin degradation product, heat shock protein-70, and suPAR were measured in 3278 patients undergoing coronary angiography. The BRS was calculated by counting the number of biomarkers above a cutoff determined using the Youden's index. Survival analyses were performed using models adjusted for traditional risk factors. A high suPAR level ≥3.5 ng/mL was associated with all-cause death and myocardial infarction (hazard ratio, 1.83; 95% confidence interval, 1.43-2.35) after adjustment for risk factors, C-reactive protein, fibrin degradation product, and heat shock protein-70. Addition of suPAR to the 3-BRS significantly improved the C statistic, integrated discrimination improvement, and net reclassification index for the primary outcome. A BRS of 1, 2, 3, or 4 was associated with a 1.81-, 2.59-, 6.17-, and 8.80-fold increase, respectively, in the risk of death and myocardial infarction. The 4-BRS was also associated with severity of coronary artery disease and composite end points. CONCLUSIONS: SuPAR is independently predictive of adverse outcomes, and its addition to a 3-BRS comprising C-reactive protein, fibrin degradation product, and heat shock protein-70 improved risk reclassification. The clinical utility of using a 4-BRS for risk prediction and management of patients with coronary artery disease warrants further study.
BACKGROUND: Inflammation, coagulation, and cell stress contribute to atherosclerosis and its adverse events. A biomarker risk score (BRS) based on the circulating levels of biomarkers C-reactive protein, fibrin degradation products, and heat shock protein-70 representing these 3 pathways was a strong predictor of future outcomes. We investigated whether soluble urokinase plasminogen activator receptor (suPAR), a marker of immune activation, is predictive of outcomes independent of the aforementioned markers and whether its addition to a 3-BRS improves risk reclassification. METHODS AND RESULTS: C-reactive protein, fibrin degradation product, heat shock protein-70, and suPAR were measured in 3278 patients undergoing coronary angiography. The BRS was calculated by counting the number of biomarkers above a cutoff determined using the Youden's index. Survival analyses were performed using models adjusted for traditional risk factors. A high suPAR level ≥3.5 ng/mL was associated with all-cause death and myocardial infarction (hazard ratio, 1.83; 95% confidence interval, 1.43-2.35) after adjustment for risk factors, C-reactive protein, fibrin degradation product, and heat shock protein-70. Addition of suPAR to the 3-BRS significantly improved the C statistic, integrated discrimination improvement, and net reclassification index for the primary outcome. A BRS of 1, 2, 3, or 4 was associated with a 1.81-, 2.59-, 6.17-, and 8.80-fold increase, respectively, in the risk of death and myocardial infarction. The 4-BRS was also associated with severity of coronary artery disease and composite end points. CONCLUSIONS: SuPAR is independently predictive of adverse outcomes, and its addition to a 3-BRS comprising C-reactive protein, fibrin degradation product, and heat shock protein-70 improved risk reclassification. The clinical utility of using a 4-BRS for risk prediction and management of patients with coronary artery disease warrants further study.
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