title: Fibro-α score as a simple and useful non-invasive test for predicting significant liver fibrosis in chronic hepatitis C patients.
abstract: OBJECTIVE
  Non-invasive methods for the assessment of liver fibrosis are clinically important where hepatitis C virus (HCV) is common in Egypt. Our aim was to evaluate the diagnostic performance of a panel of simple blood markers of liver fibrosis in chronic hepatitis C (CHC) patients.
  
  
  METHODS
  A total of 199 patients with CHC evaluated for eligibility for antiviral therapy were included. Liver biochemical profile including transaminases, bilirubin, alkaline phosphatase, serum albumin, complete blood count prothrombin time and AFP were estimated. Liver biopsy was done. Statistical analyses were performed by logistic regression and receiver operating characteristic (ROC) curves to assess and compare diagnostic accuracy of blood markers. A stepwise combination algorithm was developed and validated prospectively in 135 additional patients.
  
  
  RESULTS
  α-Foetoprotein (AFP) was the most efficient marker among other markers tested. The areas under the curves (AUCs) of AFP were 0.77 for significant liver fibrosis (F2-F4), 0.75 for advanced liver fibrosis (F3-F4) and 0.76 for liver cirrhosis (F4). The stepwise multivariate discriminant analysis (MDA) selected a novel non-invasive index for discriminating patients with significant liver fibrosis, named Fibro-α score. Fibro-α score=(1.35 (numeric constant) +AFP (IUml(-1))×0.009584+aspartate aminotransferase (AST)/alanine aminotransferase (ALT)×0.243-platelet count (×10(9)l(-1))×0.001624). The Fibro-α score was used for patients with advanced liver fibrosis and liver cirrhosis. The AUCs of Fibro-α score were 0.82 for patients with advanced liver fibrosis and 0.80 for those with cirrhosis. These results were reproduced in a validation study with no significant difference.
  
  
  CONCLUSIONS
  While liver biopsy is invasive, expensive and, in some settings, impossible to do, Fibro-α score is simple, cheap, non-invasive and may be useful for predicting significant liver fibrosis.
authors.affiliation: Research and Development Department, Biotechnology Research Center, New Damietta, Egypt.
authors.forename: Mohamed M
authors.initials: MM
authors.lastname: Omran
authors.forename: Khaled
authors.initials: K
authors.lastname: Farid
authors.forename: Tarek M
authors.initials: TM
authors.lastname: Emran
authors.forename: Ahmed A
authors.initials: AA
authors.lastname: Attallah
mesh_terms: D000328:Adult; D000410:Alanine Transaminase / Q000097:blood*; D000704:Analysis of Variance; D019540:Area Under Curve; D001219:Aspartate Aminotransferases / Q000097:blood*; D015415:Biomarkers / Q000097:blood; D005260:Female; D019698:Hepatitis C, Chronic / Q000097:blood*; D006801:Humans; D008103:Liver Cirrhosis / Q000097:blood* / Q000175:diagnosis* / Q000473:pathology; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D010976:Platelet Count; D012372:ROC Curve; D012720:Severity of Illness Index; D055815:Young Adult; D000509:alpha-Fetoproteins / Q000378:metabolism*
chemical_list: C097353:AFP protein, human; D015415:Biomarkers; D000509:alpha-Fetoproteins; D001219:Aspartate Aminotransferases; D000410:Alanine Transaminase