ArticleLiver international : official journal of the International Association for the Study of the Liver2013
Liver fibrosis staging through a stepwise analysis of non-invasive markers (FibroSteps) in patients with chronic hepatitis C infection.
Article in Liver international : official journal of the International Association for the Study of the Liver, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed.
- Article
- Associations among serum levels of MMP-1, MMP-2, and METAVIR fibrosis score in patients with nonalcoholic fatty liver disease.Gastroenterology and hepatology from bed to bench · 2025Article
- Non-alcoholic fatty liver disease: Immunological mechanisms and current treatments.World journal of gastroenterology · 2023Review
- Hepatic-Modulatory Effects of Chicken Liver Hydrolysate-Based Supplement on Autophagy Regulation against Liver Fibrogenesis.Antioxidants (Basel, Switzerland) · 2023Article
- 24-month decline of non-invasive liver fibrosis markers in HCV-mono and HCV/HIV coinfection after direct-acting antiviral therapy.Scientific reports · 2022Article
- Cost-utility analysis of four WHO-recommended sofosbuvir-based regimens for the treatment of chronic hepatitis C in sub-Saharan Africa.BMC health services research · 2022Article
- Hyaluronic acid as a biomarker of fibrosis in chronic liver diseases of different etiologies.Clujul medical (1957) · 2016Review
- miR-122 negatively correlates with liver fibrosis as detected by histology and FibroScan.World journal of gastroenterology · 2015Article
- Egy-score predicts severe hepatic fibrosis and cirrhosis in Egyptians with chronic liver diseases: a pilot study.Hepatitis monthly · 2013Article
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7 authors.
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Abstract
backgroundNon-invasive fibrosis markers can distinguish between liver fibrosis stages in lieu of liver biopsy or imaging elastography.
aimsTo develop a sensitive, non-invasive, freely-available algorithm that differentiates between individual liver fibrosis stages in chronic hepatitis C virus (HCV) patients.
methodsChronic HCV patients (n = 355) at Cairo University Hospital, Egypt, with liver biopsy to determine fibrosis stage (METAVIR), were tested for preselected fibrosis markers. A novel multistage stepwise fibrosis classification algorithm (FibroSteps) was developed using random forest analysis for biomarker selection, and logistic regression for modelling. FibroSteps predicted fibrosis stage using four steps: Step 1 distinguished no(F0)/mild fibrosis(F1) vs. moderate(F2)/severe fibrosis(F3)/cirrhosis(F4); Step 2a distinguished F0 vs. F1; Step 2b distinguished F2 vs. F3/F4; and Step 3 distinguished F3 vs. F4. FibroSteps was developed using a randomly-selected training set (n = 234) and evaluated using the remaining patients (n = 118) as a validation set.
resultsHyaluronic Acid, TGF-β1, α2-macroglobulin, MMP-2, Apolipoprotein-A1, Urea, MMP-1, alpha-fetoprotein, haptoglobin, RBCs, haemoglobin and TIMP-1 were selected into the models, which had areas under the receiver operating curve (AUC) of 0.973, 0.923 (Step 1); 0.943, 0.872 (Step 2a); 0.916, 0.883 (Step 2b) and 0.944, 0.946 (Step 3), in the training and validation sets respectively. The final classification had accuracies of 94.9% (95% CI: 91.3-97.4%) and 89.8% (95% CI: 82.9-94.6%) for the training and validation sets respectively.
conclusionsFibroSteps, a freely available, non-invasive liver fibrosis classification, is accurate and can assist clinicians in making prognostic and therapeutic decisions. The statistical code for FibroSteps using R software is provided in the supplementary materials.
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