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Contribution of the ELFG Test in Algorithms of Non-Invasive Markers towards the Diagnosis of Significant Fibrosis in Chronic Hepatitis C

BACKGROUND AND AIMS: 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. PATIENTS AND METHODS: We used the database from our study of 507 patients with histologically proven CHC in which f...

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Autores principales: Zarski, Jean-Pierre, Sturm, Nathalie, Guechot, Jérôme, Zafrani, Elie-Serge, Vaubourdolle, Michel, Thoret, Sophie, Margier, Jennifer, David-Tchouda, Sandra, Bosson, Jean-Luc
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3605459/
https://www.ncbi.nlm.nih.gov/pubmed/23555619
http://dx.doi.org/10.1371/journal.pone.0059088
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author Zarski, Jean-Pierre
Sturm, Nathalie
Guechot, Jérôme
Zafrani, Elie-Serge
Vaubourdolle, Michel
Thoret, Sophie
Margier, Jennifer
David-Tchouda, Sandra
Bosson, Jean-Luc
author_facet Zarski, Jean-Pierre
Sturm, Nathalie
Guechot, Jérôme
Zafrani, Elie-Serge
Vaubourdolle, Michel
Thoret, Sophie
Margier, Jennifer
David-Tchouda, Sandra
Bosson, Jean-Luc
author_sort Zarski, Jean-Pierre
collection PubMed
description BACKGROUND AND AIMS: 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. PATIENTS AND 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%). CONCLUSION: 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.
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spelling pubmed-36054592013-04-03 Contribution of the ELFG Test in Algorithms of Non-Invasive Markers towards the Diagnosis of Significant Fibrosis in Chronic Hepatitis C Zarski, Jean-Pierre Sturm, Nathalie Guechot, Jérôme Zafrani, Elie-Serge Vaubourdolle, Michel Thoret, Sophie Margier, Jennifer David-Tchouda, Sandra Bosson, Jean-Luc PLoS One Research Article BACKGROUND AND AIMS: 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. PATIENTS AND 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%). CONCLUSION: 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. Public Library of Science 2013-03-21 /pmc/articles/PMC3605459/ /pubmed/23555619 http://dx.doi.org/10.1371/journal.pone.0059088 Text en © 2013 Zarski et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Zarski, Jean-Pierre
Sturm, Nathalie
Guechot, Jérôme
Zafrani, Elie-Serge
Vaubourdolle, Michel
Thoret, Sophie
Margier, Jennifer
David-Tchouda, Sandra
Bosson, Jean-Luc
Contribution of the ELFG Test in Algorithms of Non-Invasive Markers towards the Diagnosis of Significant Fibrosis in Chronic Hepatitis C
title Contribution of the ELFG Test in Algorithms of Non-Invasive Markers towards the Diagnosis of Significant Fibrosis in Chronic Hepatitis C
title_full Contribution of the ELFG Test in Algorithms of Non-Invasive Markers towards the Diagnosis of Significant Fibrosis in Chronic Hepatitis C
title_fullStr Contribution of the ELFG Test in Algorithms of Non-Invasive Markers towards the Diagnosis of Significant Fibrosis in Chronic Hepatitis C
title_full_unstemmed Contribution of the ELFG Test in Algorithms of Non-Invasive Markers towards the Diagnosis of Significant Fibrosis in Chronic Hepatitis C
title_short Contribution of the ELFG Test in Algorithms of Non-Invasive Markers towards the Diagnosis of Significant Fibrosis in Chronic Hepatitis C
title_sort contribution of the elfg test in algorithms of non-invasive markers towards the diagnosis of significant fibrosis in chronic hepatitis c
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3605459/
https://www.ncbi.nlm.nih.gov/pubmed/23555619
http://dx.doi.org/10.1371/journal.pone.0059088
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