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

Autor: Alfred Gugerell, Noemi Pavo, Georgiana-Aura Giurgea, Katrin Zlabinger, Claudia Müller, Dominika Lukovic, Denise Traxler-Weidenauer, Ljubica Mandic, Andreas Spannbauer, Anahit Anvari, Nina Kastner, Jutta Bergler-Klein, Bonni Syeda, Mariann Gyöngyösi, Julia Mester-Tonczar
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Male
medicine.medical_specialty
Myocardial Infarction
lcsh:QR1-502
adverse event
Comorbidity
030204 cardiovascular system & hematology
Logistic regression
Risk Assessment
Biochemistry
Article
lcsh:Microbiology
Cohort Studies
Coronary artery disease
03 medical and health sciences
risk prediction
Percutaneous Coronary Intervention
0302 clinical medicine
Copeptin
Discriminant function analysis
Risk Factors
Internal medicine
multimarker approach
C-statistics
Clinical endpoint
medicine
Humans
Prospective Studies
030212 general & internal medicine
Myocardial infarction
Molecular Biology
Aged
Aged
80 and over
business.industry
Middle Aged
Prognosis
medicine.disease
Death
Hospitalization
Stroke
canonical discriminant analysis
SuPAR
Cardiology
Biomarker (medicine)
Female
business
Biomarkers
coronary artery disease
Zdroj: Biomolecules
Volume 10
Issue 6
Biomolecules, Vol 10, Iss 909, p 909 (2020)
ISSN: 2218-273X
DOI: 10.3390/biom10060909
Popis: 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&rsquo
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.
Databáze: OpenAIRE
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