Literature DB >> 18938750

A non-invasive fibrosis score predicts treatment outcome in chronic hepatitis C virus infection.

Johan Westin1, Magdalena Ydreborg, Sara Islam, Asa Alsiö, Amar P Dhillon, Jean-Michel Pawlotsky, Stefan Zeuzem, Solko W Schalm, Carlo Ferrari, Avidan U Neumann, Kristoffer Hellstrand, Martin Lagging.   

Abstract

OBJECTIVE: The results of a previous study suggest that an index calculated according to the formula (normalized ASAT x PK-INR) x 100/thrombocyte count (x 10(9)/L; GUCI) may reflect liver fibrosis in patients with chronic hepatitis C virus (HCV) infection. The aims of the present study were (i) to validate the association between the Göteborg University Cirrhosis Index (GUCI) score and liver fibrosis and (ii) to evaluate the utility of this index in predicting the outcome of antiviral treatment.
MATERIAL AND METHODS: A total of 269 patients with chronic HCV infection, stratified according to HCV genotype (1/4 versus 2/3) participated in a phase III trial using pegylated interferon alpha-2a and ribavirin (DITTO study). Retrospective analyses of the baseline GUCI scores and assessments of pretreatment liver biopsies using the Ishak protocol were performed. Cut-off GUCI scores were calculated to distinguish patients with a high or low probability of sustained viral response (SVR).
RESULTS: Striking associations between GUCI and Ishak fibrosis stages (stages 0-2 versus stages 3-4, p = 0.0002, stages 3-4 versus stages 5-6, p = 0.002) were observed. In patients with genotype 1 or 4, a GUCI score below 0.33 was associated with a rapid viral response to antiviral treatment and an SVR rate of 80%. Ninety-two percent of patients (92/101) with a SVR had a pretreatment GUCI score below 1.11.
CONCLUSIONS: Our results suggest that the GUCI score appropriately reflects the stage of liver fibrosis in HCV-infected patients, and predicts initial viral kinetics as well as treatment outcome in patients infected with HCV genotype 1 or 4.

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Year:  2008        PMID: 18938750     DOI: 10.1080/00365520701514461

Source DB:  PubMed          Journal:  Scand J Gastroenterol        ISSN: 0036-5521            Impact factor:   2.423


  6 in total

1.  Utility of Electronic Medical record-based Fibrosis Scores in Predicting Advanced Cirrhosis in Patients with Hepatitic C Virus Infection.

Authors:  Mohammad Qasim Khan; Vijay Anand; Norbert Hessefort; Ammar Hassan; Alya Ahsan; Amnon Sonnenberg; Claus J Fimmel
Journal:  J Transl Int Med       Date:  2017-03-31

2.  Angiopoietin-2 Serum Levels Improve Noninvasive Fibrosis Staging in Chronic Hepatitis C: A Fibrogenic-Angiogenic Link.

Authors:  Angel Hernández-Bartolomé; Rosario López-Rodríguez; Yolanda Rodríguez-Muñoz; Samuel Martín-Vílchez; María Jesús Borque; Luisa García-Buey; Leticia González-Moreno; Yolanda Real; Ricardo Moreno-Otero; Paloma Sanz-Cameno
Journal:  PLoS One       Date:  2013-06-18       Impact factor: 3.240

3.  Impact of contacting study authors to obtain additional data for systematic reviews: diagnostic accuracy studies for hepatic fibrosis.

Authors:  Shelley S Selph; Alexander D Ginsburg; Roger Chou
Journal:  Syst Rev       Date:  2014-09-19

4.  Prognostic Performance of Ten Liver Function Models in Patients with Hepatocellular Carcinoma Undergoing Radiofrequency Ablation.

Authors:  Shu-Yein Ho; Po-Hong Liu; Chia-Yang Hsu; Yi-You Chiou; Chien-Wei Su; Yun-Hsuan Lee; Yi-Hsiang Huang; Fa-Yauh Lee; Ming-Chih Hou; Teh-Ia Huo
Journal:  Sci Rep       Date:  2018-01-16       Impact factor: 4.379

5.  Comparison of twelve liver functional reserve models for outcome prediction in patients with hepatocellular carcinoma undergoing surgical resection.

Authors:  Shu-Yein Ho; Po-Hong Liu; Chia-Yang Hsu; Cheng-Yuan Hsia; Chien-Wei Su; Yun-Hsuan Lee; Yi-Hsiang Huang; Fa-Yauh Lee; Ming-Chih Hou; Teh-Ia Huo
Journal:  Sci Rep       Date:  2018-03-19       Impact factor: 4.379

6.  Current noninvasive liver reserve models do not predict histological fibrosis severity in hepatocellular carcinoma.

Authors:  Shu-Yein Ho; Po-Hong Liu; Chia-Yang Hsu; Cheng-Yuan Hsia; Chien-Wei Su; Yi-Jhen He; Yun-Hsuan Lee; Yi-Hsiang Huang; Ming-Chih Hou; Teh-Ia Huo
Journal:  Sci Rep       Date:  2018-10-10       Impact factor: 4.379

  6 in total

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