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Identification of a support vector machine-based biomarker panel with high sensitivity and specificity for nonalcoholic steatohepatitis

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dc.contributor.authorEREN, FATİH
dc.contributor.authorsYilmaz, Yusuf; Eren, Fatih
dc.date.accessioned2022-03-12T18:05:15Z
dc.date.available2022-03-12T18:05:15Z
dc.date.issued2012
dc.description.abstractBackground: 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.
dc.identifier.doi10.1016/j.cca.2012.08.005
dc.identifier.issn0009-8981
dc.identifier.pubmed22985537
dc.identifier.urihttps://hdl.handle.net/11424/230649
dc.identifier.wosWOS:000312685400032
dc.language.isoeng
dc.publisherELSEVIER SCIENCE BV
dc.relation.ispartofCLINICA CHIMICA ACTA
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectNonalcoholic steatohepatitis
dc.subjectSupport vector machine
dc.subjectBiomarkers
dc.subjectDiagnostic panel
dc.subjectFATTY LIVER-DISEASE
dc.subjectSERUM FGF21 LEVELS
dc.subjectMETABOLIC SYNDROME
dc.subjectSIMPLE STEATOSIS
dc.subjectGROWTH-FACTOR
dc.subjectDIAGNOSIS
dc.subjectFIBROSIS
dc.subjectNASH
dc.subjectCYTOKERATIN-18
dc.titleIdentification of a support vector machine-based biomarker panel with high sensitivity and specificity for nonalcoholic steatohepatitis
dc.typearticle
dspace.entity.typePublication
local.avesis.id5a13cbfa-9aee-4f67-ad12-65a41a9abdeb
local.import.packageSS17
local.indexed.atWOS
local.indexed.atSCOPUS
local.indexed.atPUBMED
local.journal.numberofpages4
oaire.citation.endPage157
oaire.citation.startPage154
oaire.citation.titleCLINICA CHIMICA ACTA
oaire.citation.volume414
relation.isAuthorOfPublication4bc77d63-5aa7-4c67-8d60-12778ea963b1
relation.isAuthorOfPublication.latestForDiscovery4bc77d63-5aa7-4c67-8d60-12778ea963b1

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