Non-Invasive Score System For Fibrosis In Chronic Hepatitis: Proposal For A Model Based On Biochemical, Fibroscan, Ultrasound Data
Silvia Gaia1,*,
Daniela Campion1,
Andrea Evangelista2,
Maurizio Spandre1,
Loretta Cosso1,
Franco Brunello1,
Giovannino Ciccone2,
Elisabetta Bugianesi1 and
Mario Rizzetto1
DOI: 10.1111/liv.12761
Vol. 34 Issue 10
Liver International
Author Information
1 Department of Gastroenterology, Città della Salute e della Scienza - University Hospital
2 Department of Epidemiology, Città della Salute e della Scienza - University Hospital, Turin, Italy
*corresponding author: md Silvia Gaia, Department of Gastroenterology, Città della Salute e della Scienza – University Hospital of Turin, c.so Bramante 88, 10100 Turin, Italy. Phone: +390116336485, fax: 0116336752, email: [email protected]
This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1111/liv.12761
Abstract
Background and Aims
We elaborate a Non-Invasive Score system for liver Fibrosis (NISF), exploring its diagnostic performance and comparing its accuracy to Fibroscan in patients with chronic viral hepatitis (CH) and Non-Alcoholic Fatty Liver Disease (NAFLD).
Methods
Clinical, biochemical, elastographic and ultrasound parameters derived from patients with CH (n=83) or NAFLD (n=58), undergoing liver biopsy for fibrosis assessment, were prospectively collected as potential predictors of fibrosis. Each parameter was evaluated for its correlation with the liver biopsy (Gold Standard). Candidate predictors with good inter-observer agreement and correlation to histological stages were combined into 2 algorithms (NISF) to predict fibrosis in chronic viral hepatitis and NAFLD.
Results
The CH-NISF included 6 parameters: bluntness of liver edges, irregularity of left lobe surface, diameter of segment 4, liver stiffness measurement, platelet count and ALT values. The ability of the model to discriminate F3-F4 vs F0-F1 stages and F2 vs F0-F1 was high (AUROC of 0.95 and 0.83, respectively) and better than Fibroscan alone, especially in intermediate stages (F2 vs F0-F1), AUROC 0.83 vs 0.57 (p 0.003). The resulting algorithm is available as mathematical formula, nomogram or free on-line links.
The NAFLD-NISF included liver stiffness, platelet count and AST levels, had good ability to discriminate F0-F1 versus F2-F3-F4 stages (AUROC 0.86), however not significantly higher than Fibroscan.
Conclusions
CH-NISF can be proposed as preliminary and easily-available staging tool, superior to Fibroscan alone in predicting histologic fibrosis, especially in intermediate stages. Further validations are needed to improve NISF accuracy in NAFLD.
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在CH-NISF包括6个参数：肝脏边缘，左叶表面不规则，部分4的直径，肝脏硬度测量，血小板计数和ALT值直率。该模型以鉴别F3-F4 VS F0-F1阶段和F2 VS F0-F1是高（0.95和0.83，分别AUROC）优于Fibroscan的单独的能力，特别是在中间级（F2 VS F0-F1）， AUROC0.83 VS0.57（P = 0.003）。所得算法可作为数学公式，列线图或免费在线连接。