Abstract
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.
Highlights
Cardiovascular mortality or morbidity risk scores are essential in primary and secondary prevention of cardiovascular adverse events (AE), and are mostly based on traditional cardiovascular risk factors, such as hypertension, diabetes mellitus, hyperlipidemia, smoking, and family history.Risk scores are created and calculated for patients with acute coronary syndrome: Thrombolysis in Myocardial Infarction (TIMI), Platelet Glycoprotein IIb/IIIa in Unstable Angina: Receptor Suppression Using Integrilin (PURSUIT), the Global Registry of Acute Coronary Events (GRACE) [1], for stable angina pectoris: Framingham Risk Score [2], Vienna and Ludwigshafen Coronary Artery Disease (VILCAD) score [3], or for general patient population, such as the SCORE-European High Risk Chart [4]
A total of 181 patients were included in the study
Due to comorbidities possibly or definitively influencing the blood levels of the selected 7 biomarkers, such as moderate to severe acute or chronic renal failure, or malignant or other chronic disease diagnosed after study inclusion, 20 patients were excluded from the biomarker measurement study
Summary
Cardiovascular mortality or morbidity risk scores are essential in primary and secondary prevention of cardiovascular adverse events (AE), and are mostly based on traditional cardiovascular risk factors, such as hypertension, diabetes mellitus, hyperlipidemia, smoking, and family history.Risk scores are created and calculated for patients with acute coronary syndrome: Thrombolysis in Myocardial Infarction (TIMI), Platelet Glycoprotein IIb/IIIa in Unstable Angina: Receptor Suppression Using Integrilin (PURSUIT), the Global Registry of Acute Coronary Events (GRACE) [1], for stable angina pectoris: Framingham Risk Score [2], Vienna and Ludwigshafen Coronary Artery Disease (VILCAD) score [3], or for general patient population, such as the SCORE-European High Risk Chart [4]. That biomarkers of inflammation, fibrinolysis or fibrin formation, endothelial function, oxidative stress, or renal or heart function parameter enhance the value of risk prediction and enable early intervention and prevention of subsequent cardiovascular adverse events (AE) [5]. Adding of routinely used biomarkers, such as troponin T or NT-pro-brain natriuretic peptide (pro-BNP) or blood cholesterol level to the traditional risk factors enhanced moderately the risk prediction in the individual patients [6]. Single or combined new biomarkers, such as copeptin, neutrophil gelatinase-associated lipocalin (NGAL), or soluble urokinase plasminogen activator receptor (suPAR) have been tested and validated in larger cohorts of patients, anticipating prognostic values of these biomarkers [7,8,9]. In contrast with single blood marker analysis, the multi-biomarker approach by using traditional or new circulating proteins might have the potential to enhance the risk stratification in individual patients
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