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Open AccessArticle

Multimarker Approach to Identify Patients with Coronary Artery Disease at High Risk for Subsequent Cardiac Adverse Events: The Multi-Biomarker Study

1
Department of Angiology, Internal Medicine II, Medical University of Vienna, 1090 Vienna, Austria
2
Department of Cardiology, Internal Medicine II, Medical University of Vienna, 1090 Vienna, Austria
*
Author to whom correspondence should be addressed.
Biomolecules 2020, 10(6), 909; https://doi.org/10.3390/biom10060909
Received: 8 May 2020 / Revised: 3 June 2020 / Accepted: 10 June 2020 / Published: 15 June 2020
(This article belongs to the Special Issue Molecular Biomarkers In Cardiology)
In our prospective non-randomized, single-center cohort study (n = 161), we have evaluated a multimarker approach including S100 calcium binding protein A12 (S100A1), interleukin 1 like-receptor-4 (IL1R4), adrenomedullin, copeptin, neutrophil gelatinase-associated lipocalin (NGAL), soluble urokinase plasminogen activator receptor (suPAR), and ischemia modified albumin (IMA) in prediction of subsequent cardiac adverse events (AE) during 1-year follow-up in patients with coronary artery disease. The primary endpoint was to assess the combined discriminatory predictive value of the selected 7 biomarkers in prediction of AE (myocardial infarction, coronary revascularization, death, stroke, and hospitalization) by canonical discriminant function analysis. The main secondary endpoints were the levels of the 7 biomarkers in the groups with/without AE; comparison of the calculated discriminant score of the biomarkers with traditional logistic regression and C-statistics. The canonical correlation coefficient was 0.642, with a Wilk’s lambda value of 0.78 and p < 0.001. By using the calculated discriminant equation with the weighted mean discriminant score (centroid), the sensitivity and specificity of our model were 79.4% and 74.3% in prediction of AE. These values were higher than that of the calculated C-statistics if traditional risk factors with/without biomarkers were used for AE prediction. In conclusion, canonical discriminant analysis of the multimarker approach is able to define the risk threshold at the individual patient level for personalized medicine. View Full-Text
Keywords: multimarker approach; adverse event; risk prediction; canonical discriminant analysis; C-statistics; coronary artery disease multimarker approach; adverse event; risk prediction; canonical discriminant analysis; C-statistics; coronary artery disease
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Giurgea, G.-A.; Zlabinger, K.; Gugerell, A.; Lukovic, D.; Syeda, B.; Mandic, L.; Pavo, N.; Mester-Tonczar, J.; Traxler-Weidenauer, D.; Spannbauer, A.; Kastner, N.; Müller, C.; Anvari, A.; Bergler-Klein, J.; Gyöngyösi, M. Multimarker Approach to Identify Patients with Coronary Artery Disease at High Risk for Subsequent Cardiac Adverse Events: The Multi-Biomarker Study. Biomolecules 2020, 10, 909.

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