The Saudi Journal of Gastroenterology (Jan 2014)

Egy-score as a noninvasive score for the assessment of hepatic fibrosis in chronic hepatitis C: A preliminary approach

  • Mohamed Alboraie,
  • Marwa Khairy,
  • Aisha Elsharkawy,
  • Marwa Elsharkawy,
  • Noha Asem,
  • Amany R. Abo El-Seoud,
  • Fathy G. Elghamry,
  • Gamal Esmat

DOI
https://doi.org/10.4103/1319-3767.133003
Journal volume & issue
Vol. 20, no. 3
pp. 170 – 174

Abstract

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Background and Aims: Egy-Score is a new noninvasive score for prediction of severe hepatic fibrosis in patients with chronic liver diseases. The aim of this study was to validate Egy-Score as a noninvasive score for predicting stage of hepatic fibrosis in a group of Egyptian chronic hepatitis C patients. Patients and Methods: One hundred Egyptian patients with chronic hepatitis C were enrolled. Mean age was 40.25 ± 9.39 years. They were subjected to CA19-9, alpha-2-macroglobulin, total bilirubin, platelet count and albumin, liver biopsy, and histopathological staging of hepatic fibrosis according to METAVIR scoring system as part of their assessment for treatment. Egy-Score was calculated according to the following formula: Egy-Score = 3.52 + 0.0063 × CA19-9 + 0.0203 × age + 0.4485 × alpha-2-macroglobulin + 0.0303 × bilirubin - 0.0048 × platelet - 0.0462 × albumin. Egy-Score results were correlated to the stage of hepatic fibrosis. Results: Egy-Score correlates positively with the stage of hepatic fibrosis (F0-F4). Egy-Score was able to differentiate significant hepatic fibrosis, severe hepatic fibrosis, and cirrhosis accurately. Cutoff values of Egy-Score were 2.91850 (for significant fibrosis), 3.28624 (for severe fibrosis), and 3.67570 (for cirrhosis). Sensitivity, specificity, and areas-under-ROC curve (AUROCs) were 75.8%, 68.42%, and 0.776 (for significant fibrosis "≥F2"), 91.67%, 77.63%, and 0.875 (for severe fibrosis "≥F3"), and 81.82%, 86.52%, and 0.874 (for cirrhosis "F4"), respectively. Conclusion: Egy-Score is a useful noninvasive panel of surrogate biomarkers that could accurately predict different stages of hepatic fibrosis in patients with chronic hepatitis C.

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