title: Usefulness of multiple biomarkers for the prediction of significant fibrosis in chronic hepatitis B.
abstract: OBJECTIVE
  It has not been explicitly addressed whether new biomarkers, in addition to readily available clinical data, make a contribution to the prediction of liver fibrosis.
  
  
  METHODS
  A total of 209 patients with chronic hepatitis B who underwent liver biopsy were recruited. The Clinical Score (CS) model using only routine clinical data and the Biomarker Score (BS) model using 7 putative biomarkers were derived from the derivation set (n=105), and these models were applied to a separate patients group (n=104) to investigate whether the addition of BS improved the diagnostic accuracy in predicting significant fibrosis beyond an assessment based solely on CS.
  
  
  RESULTS
  The most informative biomarkers for predicting significant fibrosis were hyaluronic acid and matrix metalloproteinase-2. The BS was an independent predictive factor for significant fibrosis even after accounting for CS in both sets. Among the derivation set, the incorporation of the BS into the CS model did not significantly increase the receiver operating characteristic area, with only a small improvement of about 2% (P=0.11). Similarly, in the validation set, a combined model with CS and BS showed no superior diagnostic accuracy over the CS model alone, with an improvement of approximately 2% [0.83 (0.75 to 0.92) vs. 0.81 (0.70 to 0.91); P=0.16].
  
  
  CONCLUSIONS
  The simultaneous addition of several biomarkers adds only modestly to clinical predictive factors for risk assessment of individual patients. These results highlight the need for the models to be validated in another cohort with a broader distribution of fibrosis severity.
authors.affiliation: Department of Internal Medicine, Inje University Haeundae Paik-Hospital, Busan, Korea.
authors.forename: Seung Ha
authors.initials: SH
authors.lastname: Park
authors.forename: Chang Hoon
authors.initials: CH
authors.lastname: Kim
authors.forename: Dong Joon
authors.initials: DJ
authors.lastname: Kim
authors.forename: Ki Tae
authors.initials: KT
authors.lastname: Suk
authors.forename: Jae Youn
authors.initials: JY
authors.lastname: Cheong
authors.forename: Sung Won
authors.initials: SW
authors.lastname: Cho
authors.forename: Seong Gyu
authors.initials: SG
authors.lastname: Hwang
authors.forename: Youn Jae
authors.initials: YJ
authors.lastname: Lee
authors.forename: Mong
authors.initials: M
authors.lastname: Cho
authors.forename: Jin Mo
authors.initials: JM
authors.lastname: Yang
authors.forename: Young Bae
authors.initials: YB
authors.lastname: Kim
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D015415:Biomarkers / Q000097:blood*; D005260:Female; D019694:Hepatitis B, Chronic / Q000473:pathology*; D006801:Humans; D006820:Hyaluronic Acid / Q000097:blood*; D008099:Liver / Q000473:pathology; D008103:Liver Cirrhosis / Q000175:diagnosis* / Q000473:pathology; D008297:Male; D020778:Matrix Metalloproteinase 2 / Q000097:blood*; D008875:Middle Aged; D011237:Predictive Value of Tests; D055815:Young Adult
chemical_list: D015415:Biomarkers; D006820:Hyaluronic Acid; D020778:Matrix Metalloproteinase 2