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The Performance of Enhanced Liver Fibrosis (ELF) Test for the Staging of Liver Fibrosis: A Meta-Analysis

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  • Qingsong Xie
  • Xiaohu Zhou
  • Pengfei Huang
  • Jianfeng Wei
  • Weilin Wang
  • Shusen Zheng

Abstract

Background: The enhanced liver fibrosis test (ELF) has been shown to accurately predict significant liver fibrosis in several liver diseases. Aims: To perform a meta-analysis to assess the performance of the ELF test for the assessment of liver fibrosis. Study: Electronic and manual searches were performed to identify studies of the ELF test. After methodological quality assessment and data extraction, pooled estimates of the sensitivity, specificity, area under the receiver operating characteristic curve (AUROC), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR) and summary receiver operating characteristics (sROC) were assessed systematically. The extent of heterogeneity and reasons for it were assessed. Results: Nine studies were identified for analysis. The pooled sensitivity, specificity, positive LR, negative LR, and DOR values of ELF test, for assessment of significant liver fibrosis, were 83% (95% CI = 0.80–0.86), 73% (95% CI = 0.69–0.77), 4.00 (95% CI = 2.50–6.39), 0.24 (95% CI = 0.17–0.34), and 16.10 (95% CI = 8.27–31.34), respectively; and, for evaluation of severe liver fibrosis, were 78% (95% CI = 0.74–0.81), 76% (95% CI = 0.73–0.78), 4.39 (95% CI = 2.76–6.97), 0.27 (95% CI = 0.16–0.46), and 16.01 (95% CI: 7.15–35.82), respectively; and, for estimation of cirrhosis, were 80% (95% CI = 0.75–0.85), 71% (95% CI = 0.68–0.74), 3.13 (95% CI = 2.01–4.87), 0.29 (95% CI = 0.19–0.44), and 14.09 (95% CI: 5.43–36.59), respectively. Conclusions: The ELF test shows good performance and considerable diagnostic value for the prediction of histological fibrosis stage.

Suggested Citation

  • Qingsong Xie & Xiaohu Zhou & Pengfei Huang & Jianfeng Wei & Weilin Wang & Shusen Zheng, 2014. "The Performance of Enhanced Liver Fibrosis (ELF) Test for the Staging of Liver Fibrosis: A Meta-Analysis," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-12, April.
  • Handle: RePEc:plo:pone00:0092772
    DOI: 10.1371/journal.pone.0092772
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    1. Jean-Pierre Zarski & Nathalie Sturm & Jérôme Guechot & Elie-Serge Zafrani & Michel Vaubourdolle & Sophie Thoret & Jennifer Margier & Sandra David-Tchouda & Jean-Luc Bosson, 2013. "Contribution of the ELFG Test in Algorithms of Non-Invasive Markers towards the Diagnosis of Significant Fibrosis in Chronic Hepatitis C," PLOS ONE, Public Library of Science, vol. 8(3), pages 1-7, March.
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