Identification of a support vector machine-based biomarker panel with high sensitivity and specificity for nonalcoholic steatohepatitis - EREN, FATİH; YILMAZ, YUSUF (ELSEVIER SCIENCE BV, 2012)
Background: Although liver biopsy remains the best diagnostic standard for nonalcoholic steatohepatitis (NASH), non-invasive tests are eagerly awaited. In this study, we sought to develop a support vector machine (SVM) algorithm to discriminate with high accuracy between subjects with NASH and controls using a blood-based biomarker panel. Methods: A total of 17 biomarkers were measured by commercially available enzyme-linked immunosorbent assays in 136 serum samples from patients with biopsy-proven NASH (n = 60) and subjects with normal ALT and no evidence of fatty liver on ultrasound (n = 76). The database was randomly divided (1:1 fashion) into a discovery set for classification training and in a validation set of the chosen biomarkers in blinded samples. Multivariate analysis was performed by means of SVM. Results: After the identification of a group of three most discriminative biomarkers (osteoprotegerin, fibroblast growth factor 21, and M30) in the discovery set, the application of SVM to the validation test resulted in a 92.5% sensitivity and 84.1% specificity for distinguishing subjects with NASH from controls. Conclusions: A targeted biomarker profiling combined with a SVM-based pattern identification approach may allow the identification of patients with NASH with clinically relevant accuracy and validity. (C) 2012 Elsevier B.V. All rights reserved.
Keywords: Nonalcoholic steatohepatitis; Support vector machine; Biomarkers; Diagnostic panel; FATTY LIVER-DISEASE; SERUM FGF21 LEVELS; METABOLIC SYNDROME; SIMPLE STEATOSIS; GROWTH-FACTOR; DIAGNOSIS; FIBROSIS; NASH; CYTOKERATIN-18