| Popis: |
OBJECTIVES/GOALS: To quantify changing trends in hepatocellular carcinoma (HCC) etiologies, mainly hepatitis C related HCC (HCV-HCC), nonalcoholic fatty liver disease related HCC (NAFLD-HCC), and alcoholic liver disease related HCC (ALD-HCC), at a single center as well as compared to large national databases. METHODS/STUDY POPULATION: This is a retrospective longitudinal study using a single-center database of patients presenting with HCC from January 1995 to September 2023. Etiologies were confirmed through patient history, clinical exam, and viral serologies. Trends in rate of etiology were analyzed using linear regression. Further investigation will include survival analysis. To improve generalizability, the single-center data were supplemented with national cross-sectional data from the NHANES database on liver disease prevalence from March 1999 to August 2023. Data were provided through questionnaire, clinical exam, and viral serologies. Trends in rates will be analyzed using linear regression. RESULTS/ANTICIPATED RESULTS: Among the single center cohort, NAFLD-HCC increased at an average rate of 1.3% per year (95% Confidence Interval (CI) = 1.1% to 1.4%) and HCV-HCC decreased at an average rate of -0.56% per year (95% CI = -0.83% to -0.29%). Projecting the linear models for the past ten years forward, HCV-HCC is predicted to take up a lower proportion than NASH-HCC by 2026 and lower proportion than ALD-HCC by 2028. Future results will include analysis of the changing proportions of etiologies for liver transplant and survival analysis for HCC by etiology from the single center cohort. Additionally, national trends in HCC etiologies will be provided from the NHANES database. The trends from liver transplant etiology and NHANES are expected to parallel the preliminary results. DISCUSSION/SIGNIFICANCE: As the prevalence of NAFLD increases in the general population, more cases of NAFLD-HCC will be seen in the future. Understanding the changing trends can guide surveillance recommendations, shape treatment algorithms, and frame research priorities. |
