title: Contribution of the ELFG test in algorithms of non-invasive markers towards the diagnosis of significant fibrosis in chronic hepatitis C.
abstract: OBJECTIVE
  We aimed to determine the best algorithms for the diagnosis of significant fibrosis in chronic hepatitis C (CHC) patients using all available parameters and tests.
  
  
  METHODS
  We used the database from our study of 507 patients with histologically proven CHC in which fibrosis was evaluated by liver biopsy (Metavir) and tests: Fibrometer®, Fibrotest®, Hepascore®, Apri, ELFG, MP3, Forn's, hyaluronic acid, tissue inhibitor of metalloproteinase-1 (TIMP1), MMP1, collagen IV and when possible Fibroscan™. For the first test we used 90% negative predictive value to exclude patients with F≤1, next an induction algorithm was applied giving the best tests with at least 80% positive predictive value for the diagnosis of F≥2. The algorithms were computed using the R Software C4.5 program to select the best tests and cut-offs. The algorithm was automatically induced without premises on the part of the investigators. We also examined the inter-observer variations after independent review of liver biopsies by two pathologists. A medico-economic analysis compared the screening strategies with liver biopsy.
  
  
  RESULTS
  In "intention to diagnose" the best algorithms for F≥2 were Fibrometer ®, Fibrotest®, or Hepascore® in first intention with the ELFG score in second intention for indeterminate cases. The percentage of avoided biopsies varied between 50% (Fibrotest® or Fibrometer®+ELFG) and 51% (Hepascore®+ELFG). In "per-analysis" Fibroscan™+ELFG avoided liver biopsy in 55% of cases. The diagnostic performance of these screening strategies was statistically superior to the usual combinations (Fibrometer® or Fibrotest®+Fibroscan™) and was cost effective. We note that the consensual review of liver biopsies between the two pathologists was mainly in favor of F1 (64-69%).
  
  
  CONCLUSIONS
  The ELFG test could replace Fibroscan in most currently used algorithms for the diagnosis of significant fibrosis including for those patients for whom Fibroscan™ is unusable.
authors.affiliation: Hepato-Gastroenterology Clinic, DIGIDUNE Pole, Grenoble University Hospital, Grenoble, France. JPZarski@chu-grenoble.fr
authors.forename: Jean-Pierre
authors.initials: JP
authors.lastname: Zarski
authors.forename: Nathalie
authors.initials: N
authors.lastname: Sturm
authors.forename: Jérôme
authors.initials: J
authors.lastname: Guechot
authors.forename: Elie-Serge
authors.initials: ES
authors.lastname: Zafrani
authors.forename: Michel
authors.initials: M
authors.lastname: Vaubourdolle
authors.forename: Sophie
authors.initials: S
authors.lastname: Thoret
authors.forename: Jennifer
authors.initials: J
authors.lastname: Margier
authors.forename: Sandra
authors.initials: S
authors.lastname: David-Tchouda
authors.forename: Jean-Luc
authors.initials: JL
authors.lastname: Bosson
mesh_terms: D000465:Algorithms; D015415:Biomarkers / Q000097:blood; D001706:Biopsy; D054459:Elasticity Imaging Techniques; D019698:Hepatitis C, Chronic / Q000150:complications*; D006801:Humans; D008099:Liver / Q000473:pathology; D008103:Liver Cirrhosis / Q000097:blood / Q000175:diagnosis* / Q000209:etiology*; D025341:Principal Component Analysis
chemical_list: D015415:Biomarkers
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