Cost Effective Non Invasive Diagnostic Modalities and Predictive Model for Development and Progression of Fibrosis Among Patients With Hepatitis B, Hepatitis C Infection or Non Alcoholic Fatty Liver Disease: A Hospital Based Retrospective Followed by Prospective Cohort Study
Cost Effective Non Invasive Diagnostic Modalities and Predictive Model for Development and Progression of Fibrosis Among Patients With Hepatitis B, Hepatitis C Infection or Non Alcoholic Fatty Liver Disease: A Hospital Based Retrospective Followed by Prospective Cohort Study
Chronic liver diseases of differing etiologies are among the leading causes of morbidity and mortality worldwide [1]. Chronic liver disease progresses through different pathological stages that vary from mild hepatic inflammation without fibrosis to advanced hepatic fibrosis and cirrhosis [2]. Assessment of the stage of liver disease is important for diagnosis, treatment, and follow-up both during treatment and after cessation of treatment. A liver biopsy is the oldest and most accurate method used to evaluate liver histology and the progression of chronic liver disease. Furthermore, different histological scoring systems have been developed and modified [3]. A liver biopsy is considered the gold standard for assessing liver histology [4]. During the pathological progression of liver fibrosis, excessive amounts of extracellular matrix build up; furthermore, serum levels of various biomarkers change, in addition to the appearance of new biomarkers in the serum during the different stages of fibrosis [2, 5]. Recently many noninvasive markers (NIMs) for assessing liver fibrosis have been developed, and they are frequently used in clinical practice. They have been validated in different studies, and some were found to be highly accurate in the assessment of liver fibrosis compared with liver biopsies [6-7], which have always been used as the standard reference method for evaluating the accuracy of noninvasive methods. There are limited studies documenting the cost effectiveness of non invasive markers over invasive technique.
Most people with chronic Hepatitis B or C are unaware of their infection, putting them at serious risk of developing cirrhosis or liver cancer which are life threatening. Similarly patients with non alcoholic fatty liver diseases are unaware about fibrosis in liver. About 20-50% of persistent infection ends up into fibrosis and finally cirrhosis. Invasive and non invasive diagnostic methods are widely used to detect the fibrosis. Clinicians use different drugs and combinations to treat HBV and HCV infections. However, there is scarcity of a longitudinal prospective study to assess the cost effectiveness of these diagnostic measures.
We planned to conduct a retrospective followed by prospective cohort study among all cases that underwent biopsy in ILBS or GB Pant Hospital since 2000 till Dec 2020 with HBV infection, HCV infection, or non alcoholic fatty liver disease. For retrospective cohort study, we will collect data from hospital information system for all patients with HBV infection, HCV infection, or non alcoholic fatty liver disease, who underwent biopsy during the period of 2000-Dec 2015. The new patients with HBV infection, HCV infection, or non alcoholic fatty liver disease who will undergo biopsy during the period Jan 2016- Dec 2020 will serve as a cohort for prospective design.
We will collect socio-demographic data, clinical data, family history, personal history, medical history, anthropometry, biochemical and radiological data from each patient. We will also be conducting a cost effective analysis for various non invasive markers against biopsy as a gold standard in predicting fibrosis, both for retrospective and prospective cohorts.
For prospective cohort study, after evaluation of baseline biopsy results, the cases with metavir fibrosis score (F0-3) will be followed for a period of 5 years to document incidence of development and progression of fibrosis.
No additional investigation or test will be asked to the patient for the study. We will also develop a predicting model for development and progression of fibrosis.
Inclusion Criteria:
Exclusion Criteria: