Detailed Information

Cited 10 time in webofscience Cited 10 time in scopus
Metadata Downloads

A Practical Scoring System for Predicting Cirrhosis in Patients with Chronic Viral Hepatitis

Authors
Cheong, Jae YounUm, Soon HoSeo, Yeon SeokShin, Seung SooPark, Rae WoongKim, Dong JoonHwang, Seong GyuLee, Youn JaeCho, MongYang, Jin MoKim, Young BaePark, Young NyunCho, Sung Won
Issue Date
Nov-2012
Publisher
H G E UPDATE MEDICAL PUBLISHING S A
Keywords
Chronic hepatitis; Liver fibrosis; Hyaluronic acid; Procollagen III N-terminal peptide; Decision tree algorithm
Citation
HEPATO-GASTROENTEROLOGY, v.59, no.120, pp.2592 - 2597
Indexed
SCIE
SCOPUS
Journal Title
HEPATO-GASTROENTEROLOGY
Volume
59
Number
120
Start Page
2592
End Page
2597
URI
https://scholarworks.korea.ac.kr/kumedicine/handle/2020.sw.kumedicine/11612
DOI
10.5754/hge10157
ISSN
0172-6390
Abstract
Background/Aims: The purpose of the current study was to develop a simple model for predicting cirrhosis in chronic viral hepatitis patients and to evaluate the usefulness of decision tree algorithms. Methodology: Serum markers of fibrosis were compared with the stage of fibrosis in liver biopsy specimens prospectively obtained from 526 subjects with chronic HBV and HCV infections (estimation set, 367; validation set, 159). Results: Univariate analysis revealed that age, bilirubin, platelet count, APRI, ALP, hyaluronic acid (HA), alpha 2-macroglobulin, MMP-2, TIMP-1, and procollagen III N-terminal peptide (PIIINP) were significantly different between patients with (F4) and without cirrhosis (F0123). Multivariate logistic regression analysis identified platelet count, HA and PIIINP as independent predictors of cirrhosis. We categorized the individual variable into the most appropriate cut-off value by calculating the likelihood ratio for predicting cirrhosis and constructed a score system expressed by the following simple formula: PHP index = platelet score + HA score + PIIINP score. For predicting cirrhosis, the area under the receiver operating characteristic curve (AUROC) was 0.824 and 0.759 in the estimation and validation set, respectively. Using a cutoff score of 4, the presence of cirrhosis was predicted with high accuracy. The diagnostic performance of the PHP index was similar to decision tree algorithms (AUROC=0.819) for predicting liver cirrhosis, but more useful in clinical situations. Conclusions: Compared to a decision tree model, a simple score system using a categorized value based on a combination of platelet count, HA and PIIINP identified patients with liver cirrhosis with a higher clinical usability.
Files in This Item
There are no files associated with this item.
Appears in
Collections
2. Clinical Science > Department of Gastroenterology and Hepatology > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Seo, Yeon Seok photo

Seo, Yeon Seok
Anam Hospital (Department of Gastroenterology and Hepatology, Anam Hospital)
Read more

Altmetrics

Total Views & Downloads

BROWSE