Dataset Information

Liver fibrosis staging through a stepwise analysis of non-invasive markers (FibroSteps) in patients with chronic hepatitis C infection.

ABSTRACT:

Background

Non-invasive fibrosis markers can distinguish between liver fibrosis stages in lieu of liver biopsy or imaging elastography.

Aims

To develop a sensitive, non-invasive, freely-available algorithm that differentiates between individual liver fibrosis stages in chronic hepatitis C virus (HCV) patients.

Methods

Chronic 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.

Results

Hyaluronic 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.

Conclusions

FibroSteps, 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.

SUBMITTER: El-Kamary SS

PROVIDER: S-EPMC3793639 | biostudies-literature | 2013 Aug

REPOSITORIES: biostudies-literature

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Publications

Liver fibrosis staging through a stepwise analysis of non-invasive markers (FibroSteps) in patients with chronic hepatitis C infection.

El-Kamary Samer S SS Mohamed Mona M MM El-Raziky Maissa M Shardell Michelle D MD Shaker Olfat G OG ElAkel Wafaa A WA Esmat Gamal G

Liver international : official journal of the International Association for the Study of the Liver 20130320 7

<h4>Background</h4>Non-invasive fibrosis markers can distinguish between liver fibrosis stages in lieu of liver biopsy or imaging elastography.<h4>Aims</h4>To develop a sensitive, non-invasive, freely-available algorithm that differentiates between individual liver fibrosis stages in chronic hepatitis C virus (HCV) patients.<h4>Methods</h4>Chronic HCV patients (n = 355) at Cairo University Hospital, Egypt, with liver biopsy to determine fibrosis stage (METAVIR), were tested for preselected fibro ...[more]

PMID: 23509874

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Project description:BackgroundIn the absence of liver biopsy, the World Health Organization recommends non-invasive tests, such as aspartate aminotransferase to platelet ratio index and FIB-4, to assess liver fibrosis in patients with chronic hepatitis B. However, these tests are not well validated in sub-Saharan Africa. Recently, a new marker, gamma-glutamyl transpeptidase to platelet ratio, was found to be more accurate in an African setting, but this needs confirmation in other cohorts.MethodsA treatment program for chronic hepatitis B was initiated in Addis Ababa, Ethiopia, in 2015. Non-invasive tests were compared with transient elastography (Fibroscan 402, Echosense, France) using the following thresholds: no fibrosis (≤7.9 kPa), significant fibrosis (>7.9 kPa) and cirrhosis (>11.7 kPa). The diagnostic accuracy was estimated by calculating the area under the receiver operating characteristics curve.ResultsOf 582 treatment-naïve patients, 141 (24.2%) had significant fibrosis and 90 (15.5%) had cirrhosis. The area under the receiver operating characteristics curve of aspartate aminotransferase to platelet ratio index, FIB-4 and gamma-glutamyl transpeptidase to platelet ratio was high both to diagnose significant fibrosis (0.79 [95% CI 0.75-0.84], 0.79 [95% CI 0.75-0.84], 0.80 [95% CI 0.75-0.85]) and cirrhosis (0.86 [95% CI 0.81-0.91], 0.86 [95% CI 0.81-0.91], 0.87 [95% CI 0.82-0.91]). The specificity was high for all tests (94%-100%); however, the sensitivity was poor both to detect fibrosis (10%-45%) and cirrhosis (10%-36%).ConclusionsAspartate aminotransferase to platelet ratio index, FIB-4 and gamma-glutamyl transpeptidase to platelet ratio had good diagnostic properties to detect liver fibrosis and cirrhosis in patients with chronic hepatitis B in East Africa. However, the sensitivity was low, and only 10% of patients with cirrhosis were detected using aspartate aminotransferase to platelet ratio index at the World Health Organization recommended threshold.

Project description:BACKGROUND: Chronic infection with hepatitis C virus (HCV) is a risk factor for liver diseases such as fibrosis, cirrhosis and hepatocellular carcinoma. HCV genetic heterogeneity was hypothesized to be associated with severity of liver disease. However, no reliable viral markers predicting disease severity have been identified. Here, we report the utility of sequences from 3 HCV 1b genomic regions, Core, NS3 and NS5b, to identify viral genetic markers associated with fast and slow rate of fibrosis progression (RFP) among patients with and without liver transplantation (n = 42). METHODS: A correlation-based feature selection (CFS) method was used to detect and identify RFP-relevant viral markers. Machine-learning techniques, linear projection (LP) and Bayesian Networks (BN), were used to assess and identify associations between the HCV sequences and RFP. RESULTS: Both clustering of HCV sequences in LP graphs using physicochemical properties of nucleotides and BN analysis using polymorphic sites showed similarities among HCV variants sampled from patients with a similar RFP, while distinct HCV genetic properties were found associated with fast or slow RFP. Several RFP-relevant HCV sites were identified. Computational models parameterized using the identified sites accurately associated HCV strains with RFP in 70/30 split cross-validation (90-95% accuracy) and in validation tests (85-90% accuracy). Validation tests of the models constructed for patients with or without liver transplantation suggest that the RFP-relevant genetic markers identified in the HCV Core, NS3 and NS5b genomic regions may be useful for the prediction of RFP regardless of transplant status of patients. CONCLUSIONS: The apparent strong genetic association to RFP suggests that HCV genetic heterogeneity has a quantifiable effect on severity of liver disease, thus presenting opportunity for developing genetic assays for measuring virulence of HCV strains in clinical and public health settings.

Project description:OBJECTIVES:The aim of this study was to explore the association of serum fibrosis marker levels with the risk of clinical and histological disease progression in a large cohort of patients with chronic hepatitis C (CHC). METHODS:462 prior non-responders to peginterferon and ribavirin enrolled in the randomised phase of the Hepatitis C Antiviral Long-term Treatment against Cirrhosis (HALT-C) Trial had baseline and annual serum samples tested for hyaluronic acid (HA), N-terminal peptide of procollagen type 3, tissue inhibitor of matrix metalloproteinase-1 (TIMP-1) and YKL-40. All patients underwent a pretreatment liver biopsy and follow-up biopsies at years 2 and 4. Histological progression was defined as a ?2 point increase in Ishak fibrosis score in patients without cirrhosis. Clinical outcomes included development of decompensation, hepatocellular cancer, death or an increase in the CTP (Child-Turcotte-Pugh) score to ?7. RESULTS:Mean patient age was 49.5 years and 39% had histological cirrhosis at entry. Baseline HA, YKL-40 and TIMP-1 levels combined with other laboratory parameters were all significantly associated with clinical outcomes in the 69 (15%) patients with disease progression (p<0.0001). The best multivariate model to predict clinical outcomes included baseline bilirubin, albumin, international normalised ratio (INR) and YKL-40 levels. All of the baseline serum fibrosis marker levels were also significantly associated with histological fibrosis progression that developed in 70 (33%) of the 209 patients with cirrhosis (p <0.0001). However, baseline HA and platelet counts were best at predicting histological progression (area under the curve (AUC)=0.663). CONCLUSION:Pretreatment serum fibrosis marker levels are significantly increased in patients with CHC at risk of clinical and histological disease progression. If validated in additional cohorts, measurement of these markers could help identify patients with CHC who would benefit from more frequent and intensive monitoring.

Dataset Information

Liver fibrosis staging through a stepwise analysis of non-invasive markers (FibroSteps) in patients with chronic hepatitis C infection.

Background

Aims

Methods

Results

Conclusions

Publications

Liver fibrosis staging through a stepwise analysis of non-invasive markers (FibroSteps) in patients with chronic hepatitis C infection.

Similar Datasets

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