Document Detail

Identification of a support vector machine-based biomarker panel with high sensitivity and specificity for nonalcoholic steatohepatitis.
MedLine Citation:
PMID:  22985537     Owner:  NLM     Status:  Publisher    
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.
Yusuf Yilmaz; Fatih Eren
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-8-17
Journal Detail:
Title:  Clinica chimica acta; international journal of clinical chemistry     Volume:  -     ISSN:  1873-3492     ISO Abbreviation:  Clin. Chim. Acta     Publication Date:  2012 Aug 
Date Detail:
Created Date:  2012-9-18     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  1302422     Medline TA:  Clin Chim Acta     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
Copyright © 2012. Published by Elsevier B.V.
Department of Gastroenterology, Marmara University School of Medicine, Istanbul, Turkey; Institute of Gastroenterology, Marmara University, Istanbul, Turkey.
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