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This is an observational study to identify the prevalence of advanced liver fibrosis among patients with excessive alcohol intake using a non-invasive method (FibroScan®) and to characterize the main environmental, genetic and epigenetic factors that could influence the development of advanced fibrosis.
The investigators will include patients 21 years of age or older with excessive alcohol intake, with abnormal AST, ALT, GGT and/or bilirubin, and without any evidence of decompensated liver disease (jaundice, ascites, encephalopathy).
Liver fibrosis will be estimated by FibroScan®. A designed questionnaire for studying environmental and psychosocial factors will be filled by the included patients, and blood samples will be obtained to study genetic and epigenetic factors.
The patients with advance fibrosis will be referred to the specialist for surveillance and treatment according to current clinical guidelines.
Full description
Background:
The Global Status Report on Alcohol and Health 2014 from the World Health Organization indicates that alcohol abuse accounts for 50% of cirrhosis worldwide. Therefore, alcoholic liver disease (ALD) is a main cause of advanced liver fibrosis globally. ALD encompasses a range of disorders including simple steatosis, alcoholic steatohepatitis, fibrosis, cirrhosis, and hepatocellular carcinoma. In addition, patients with underlying ALD and active drinking can develop an episode of acute-on-chronic liver injury called "alcoholic hepatitis", which portends a poor prognosis.
Most patients with ALD are identified during the late stages of the disease when liver decompensation occurs. In fact, a recent global epidemiologic study (GLADIS) showed that ALD is by far the liver disease that is detected at the latest stages (ratio of early/late referral negative 8-fold). These results strongly suggest that there is a dire need for the early detection of ALD patients, which currently is almost nonexistent.
A non-invasive method to screen for advanced fibrosis and cirrhosis is transient elastography (FibroScan®). This modality could potentially diagnose silent liver disease among heavy drinkers, allowing for earlier referral to a specialty liver clinic for further treatment.
Individual susceptibility to the development of advanced fibrosis among heavy drinkers is likely determined by a combination of environmental, genetic and epigenetic factors, yet the mechanisms are largely unknown.
Exposing the exact risk factors for the progression of subclinical liver disease to advanced fibrosis and cirrhosis among heavy alcohol users may assist with prognostication and help influence a patient's decision to abstain from alcohol.
The main goal of this study is to identify the prevalence of advanced liver fibrosis (F3 y F4) among patients with excessive alcohol intake using a non-invasive method (FibroScan®) and refer those who already have evidence of advanced fibrosis (F3-4 stage) to a specialized ALD clinic for treatment. The secondary goal is, to identify the main psychosocial, environmental, genetic and epigenetic factors that influence the individual susceptibility to develop advanced ALD and design a risk algorithm taking into account the interaction between these factors.
Design: This is a prospective observational single center study.
Length of participation:
End of the study: The duration of the project is expected to be two years.
Study development: Patients will be recruited within UPMC Presbyterian (Oakland) and UPMC McKeesport.
Study procedures:
Statistics:
General features and characteristics of the analysis:
Descriptive statistics will be used to report baseline characteristics of our study population as well as the incidence and prevalence of variables of interest. Chi-square test will be used to compare frequency distributions between subgroups for categorical variables. Mann-Whitney U will be used to compare continuous variables when variables do not follow normal distributions. Univariate analyses, using Chi-square, Student's t-test and Mann-Whitney U test will be used to assess the association between potential factors and advanced fibrosis. Logistic regression models will be fitted to select the best subset of predictors for advanced fibrosis. Those factors showing a clinically and statistically significant association with the outcome in univariate analyses will be selected for the initial models. The final models will be fitted by using a step-wise forward method based on model Likelihood Ratios with the same significance level (p<0.05) for entering and dropping variables. The significance level will be set at p<0.05 for all the analyses. Statistical analyses will be performed using IBM SPSS Statistics.
Sample size:
The investigators calculated a sample size of 350 subjects. An interim analysis will be performed.
Direct access to data source:
Clinical data will be collected into a web-based and HIPAA-compatible database system. The information will be registered in the electronic record system, Research Electronic Data Capture (REDCap), which has been validated by the ERIS / EDC Support team to ensure HIPAA compliance. REDCap is also assessed by the Partners Information Security Risk Assessment Team to ensure compliance with all Partners HealthCare policies.
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Data sourced from clinicaltrials.gov
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