A novel fibrosis index comprising a non-cholesterol sterol accurately predicts HCV-related liver cirrhosis.

Diagnosis of liver cirrhosis is essential in the management of chronic hepatitis C virus (HCV) infection. Liver biopsy is invasive and thus entails a risk of complications as well as a potential risk of sampling error. Therefore, non-invasive diagnostic tools are preferential. The aim of the present...

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Main Authors: Magdalena Ydreborg, Vera Lisovskaja, Martin Lagging, Peer Brehm Christensen, Nina Langeland, Mads Rauning Buhl, Court Pedersen, Kristine Mørch, Rune Wejstål, Gunnar Norkrans, Magnus Lindh, Martti Färkkilä, Johan Westin
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2014-01-01
Series:PLoS ONE
Online Access:https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0093601&type=printable
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author Magdalena Ydreborg
Vera Lisovskaja
Martin Lagging
Peer Brehm Christensen
Nina Langeland
Mads Rauning Buhl
Court Pedersen
Kristine Mørch
Rune Wejstål
Gunnar Norkrans
Magnus Lindh
Martti Färkkilä
Johan Westin
author_facet Magdalena Ydreborg
Vera Lisovskaja
Martin Lagging
Peer Brehm Christensen
Nina Langeland
Mads Rauning Buhl
Court Pedersen
Kristine Mørch
Rune Wejstål
Gunnar Norkrans
Magnus Lindh
Martti Färkkilä
Johan Westin
author_sort Magdalena Ydreborg
collection DOAJ
description Diagnosis of liver cirrhosis is essential in the management of chronic hepatitis C virus (HCV) infection. Liver biopsy is invasive and thus entails a risk of complications as well as a potential risk of sampling error. Therefore, non-invasive diagnostic tools are preferential. The aim of the present study was to create a model for accurate prediction of liver cirrhosis based on patient characteristics and biomarkers of liver fibrosis, including a panel of non-cholesterol sterols reflecting cholesterol synthesis and absorption and secretion. We evaluated variables with potential predictive significance for liver fibrosis in 278 patients originally included in a multicenter phase III treatment trial for chronic HCV infection. A stepwise multivariate logistic model selection was performed with liver cirrhosis, defined as Ishak fibrosis stage 5-6, as the outcome variable. A new index, referred to as Nordic Liver Index (NoLI) in the paper, was based on the model: Log-odds (predicting cirrhosis) = -12.17+ (age × 0.11) + (BMI (kg/m(2)) × 0.23) + (D7-lathosterol (μg/100 mg cholesterol)×(-0.013)) + (Platelet count (x10(9)/L) × (-0.018)) + (Prothrombin-INR × 3.69). The area under the ROC curve (AUROC) for prediction of cirrhosis was 0.91 (95% CI 0.86-0.96). The index was validated in a separate cohort of 83 patients and the AUROC for this cohort was similar (0.90; 95% CI: 0.82-0.98). In conclusion, the new index may complement other methods in diagnosing cirrhosis in patients with chronic HCV infection.
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spelling doaj-art-35eef602e7e04248abd8eba98092990d2025-08-20T03:00:34ZengPublic Library of Science (PLoS)PLoS ONE1932-62032014-01-0194e9360110.1371/journal.pone.0093601A novel fibrosis index comprising a non-cholesterol sterol accurately predicts HCV-related liver cirrhosis.Magdalena YdreborgVera LisovskajaMartin LaggingPeer Brehm ChristensenNina LangelandMads Rauning BuhlCourt PedersenKristine MørchRune WejstålGunnar NorkransMagnus LindhMartti FärkkiläJohan WestinDiagnosis of liver cirrhosis is essential in the management of chronic hepatitis C virus (HCV) infection. Liver biopsy is invasive and thus entails a risk of complications as well as a potential risk of sampling error. Therefore, non-invasive diagnostic tools are preferential. The aim of the present study was to create a model for accurate prediction of liver cirrhosis based on patient characteristics and biomarkers of liver fibrosis, including a panel of non-cholesterol sterols reflecting cholesterol synthesis and absorption and secretion. We evaluated variables with potential predictive significance for liver fibrosis in 278 patients originally included in a multicenter phase III treatment trial for chronic HCV infection. A stepwise multivariate logistic model selection was performed with liver cirrhosis, defined as Ishak fibrosis stage 5-6, as the outcome variable. A new index, referred to as Nordic Liver Index (NoLI) in the paper, was based on the model: Log-odds (predicting cirrhosis) = -12.17+ (age × 0.11) + (BMI (kg/m(2)) × 0.23) + (D7-lathosterol (μg/100 mg cholesterol)×(-0.013)) + (Platelet count (x10(9)/L) × (-0.018)) + (Prothrombin-INR × 3.69). The area under the ROC curve (AUROC) for prediction of cirrhosis was 0.91 (95% CI 0.86-0.96). The index was validated in a separate cohort of 83 patients and the AUROC for this cohort was similar (0.90; 95% CI: 0.82-0.98). In conclusion, the new index may complement other methods in diagnosing cirrhosis in patients with chronic HCV infection.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0093601&type=printable
spellingShingle Magdalena Ydreborg
Vera Lisovskaja
Martin Lagging
Peer Brehm Christensen
Nina Langeland
Mads Rauning Buhl
Court Pedersen
Kristine Mørch
Rune Wejstål
Gunnar Norkrans
Magnus Lindh
Martti Färkkilä
Johan Westin
A novel fibrosis index comprising a non-cholesterol sterol accurately predicts HCV-related liver cirrhosis.
PLoS ONE
title A novel fibrosis index comprising a non-cholesterol sterol accurately predicts HCV-related liver cirrhosis.
title_full A novel fibrosis index comprising a non-cholesterol sterol accurately predicts HCV-related liver cirrhosis.
title_fullStr A novel fibrosis index comprising a non-cholesterol sterol accurately predicts HCV-related liver cirrhosis.
title_full_unstemmed A novel fibrosis index comprising a non-cholesterol sterol accurately predicts HCV-related liver cirrhosis.
title_short A novel fibrosis index comprising a non-cholesterol sterol accurately predicts HCV-related liver cirrhosis.
title_sort novel fibrosis index comprising a non cholesterol sterol accurately predicts hcv related liver cirrhosis
url https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0093601&type=printable
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