ArticlePloS one2013
Contribution of the ELFG test in algorithms of non-invasive markers towards the diagnosis of significant fibrosis in chronic hepatitis C.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.
- The performance of enhanced liver fibrosis (ELF) test for the staging of liver fibrosis: a meta-analysis.PloS one · 2014Pooled it
- Enhanced Liver Fibrosis Score: Is It Useful for Evaluation of Fibrosis Severity in Chronic Hepatitis C Infection?Cureus · 2022Article
- Overestimate of Fibrosis by FIBROSpect® II in African Americans Complicates the Management of their Chronic Hepatitis C.Journal of clinical and translational hepatology · 2016Article
- Non-invasive assessment of liver fibrosis: Between prediction/prevention of outcomes and cost-effectiveness.World journal of gastroenterology · 2016Review
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Authors and funding
9 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
aimsWe 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
methodsWe 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.
resultsIn "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%).
conclusionThe 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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