PLoS ONE (Jan 2014)

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

  • 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

DOI
https://doi.org/10.1371/journal.pone.0093601
Journal volume & issue
Vol. 9, no. 4
p. e93601

Abstract

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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.