Eur Rev Med Pharmacol Sci 2016; 20 (6): 1037-1043

Quantitative fibrosis parameters highly predict esophageal-gastro varices in primary biliary cirrhosis

Q.-M. Wu, X.-Y. Zhao, H. You

Liver Research Center, Beijing Friendship Hospital, Capital Medical University, Beijing, China. hongyou30@sina.com


OBJECTIVE: Esophageal-gastro Varices (EGV) may develop in any histological stages of primary biliary cirrhosis (PBC). We aim to establish and validate quantitative fibrosis (qFibrosis) parameters in portal, septal and fibrillar areas as ideal predictors of EGV in PBC patients.

PATIENTS AND METHODS: PBC patients with liver biopsy, esophagogastroscopy and Second Harmonic Generation (SHG)/Two-photon Excited Fluorescence (TPEF) microscopy images were retrospectively enrolled in this study. qFibrosis parameters in portal, septal and fibrillar areas were acquired by computer-assisted SHG/TPEF imaging system. Independent predictor was identified using multivariate logistic regression analysis.

RESULTS: Among the forty-nine PBC patients with qFibrosis images, twenty-nine PBC patients with both esophagogastroscopy data and qFibrosis data were selected out for EGV prognosis analysis and 44.8% (13/29) of them had EGV. The qFibrosis parameters of collagen percentage and number of crosslink in fibrillar area, short/long/thin strings number and length/width of the strings in septa area were associated with EGV (p < 0.05). Multivariate logistic analysis showed that the collagen percentage in fibrillar area ≥ 3.6% was an independent factor to predict EGV (odds ratio 6.9; 95% confidence interval 1.6-27.4). The area under receiver operating characteristic (ROC), diagnostic sensitivity and specificity was 0.9, 100% and 75% respectively.

CONCLUSIONS: Collagen percentage in the fibrillar area as an independent predictor can highly predict EGV in PBC patients.

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To cite this article

Q.-M. Wu, X.-Y. Zhao, H. You
Quantitative fibrosis parameters highly predict esophageal-gastro varices in primary biliary cirrhosis

Eur Rev Med Pharmacol Sci
Year: 2016
Vol. 20 - N. 6
Pages: 1037-1043