title: Simpler score of routine laboratory tests predicts liver fibrosis in patients with chronic hepatitis B.
abstract: OBJECTIVE
  In recent years, a great interest has been dedicated to the development of noninvasive predictive models to substitute liver biopsy for fibrosis assessment and follow-up. Our aim was to provide a simpler model consisting of routine laboratory markers for predicting liver fibrosis in patients chronically infected with hepatitis B virus (HBV) in order to optimize their clinical management.
  
  
  METHODS
  Liver fibrosis was staged in 386 chronic HBV carriers who underwent liver biopsy and routine laboratory testing. Correlations between routine laboratory markers and fibrosis stage were statistically assessed. After logistic regression analysis, a novel predictive model was constructed. This S index was validated in an independent cohort of 146 chronic HBV carriers in comparison to the SLFG model, Fibrometer, Hepascore, Hui model, Forns score and APRI using receiver operating characteristic (ROC) curves.
  
  
  RESULTS
  The diagnostic values of each marker panels were better than single routine laboratory markers. The S index consisting of gamma-glutamyltransferase (GGT), platelets (PLT) and albumin (ALB) (S-index: 1000 x GGT/(PLT x ALB(2))) had a higher diagnostic accuracy in predicting degree of fibrosis than any other mathematical model tested. The areas under the ROC curves (AUROC) were 0.812 and 0.890 for predicting significant fibrosis and cirrhosis in the validation cohort, respectively.
  
  
  CONCLUSIONS
  The S index, a simpler mathematical model consisting of routine laboratory markers predicts significant fibrosis and cirrhosis in patients with chronic HBV infection with a high degree of accuracy, potentially decreasing the need for liver biopsy.
authors.affiliation: Department of Gastroenterology, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
authors.forename: Kun
authors.initials: K
authors.lastname: Zhou
authors.forename: Chun-Fang
authors.initials: CF
authors.lastname: Gao
authors.forename: Yun-Peng
authors.initials: YP
authors.lastname: Zhao
authors.forename: Hai-Lin
authors.initials: HL
authors.lastname: Liu
authors.forename: Rui-Dan
authors.initials: RD
authors.lastname: Zheng
authors.forename: Jian-Chun
authors.initials: JC
authors.lastname: Xian
authors.forename: Hong-Tao
authors.initials: HT
authors.lastname: Xu
authors.forename: Yi-Min
authors.initials: YM
authors.lastname: Mao
authors.forename: Min-De
authors.initials: MD
authors.lastname: Zeng
authors.forename: Lun-Gen
authors.initials: LG
authors.lastname: Lu
mesh_terms: D000328:Adult; D015415:Biomarkers / Q000097:blood; D001706:Biopsy; D016009:Chi-Square Distribution; D002681:China; D005260:Female; D006305:Health Status Indicators; D019694:Hepatitis B, Chronic / Q000150:complications*; D006801:Humans; D008099:Liver / Q000201:enzymology* / Q000473:pathology / Q000821:virology; D008103:Liver Cirrhosis / Q000097:blood / Q000175:diagnosis* / Q000473:pathology / Q000821:virology; D016015:Logistic Models; D008297:Male; D010976:Platelet Count; D011237:Predictive Value of Tests; D011379:Prognosis; D011446:Prospective Studies; D012372:ROC Curve; D015203:Reproducibility of Results; D012709:Serum Albumin / Q000032:analysis*; D012720:Severity of Illness Index; D055815:Young Adult; D005723:gamma-Glutamyltransferase / Q000097:blood*
chemical_list: D015415:Biomarkers; D012709:Serum Albumin; D005723:gamma-Glutamyltransferase