ISSN: 0970-938X (Print) | 0976-1683 (Electronic)

Biomedical Research

An International Journal of Medical Sciences

Abstract

Cost-effectiveness of image-based surveillance for hepatocellular carcinoma in cirrhotic patients: a systematic review

This study aims to summarize cost-effectiveness analyses assessing image-based surveillance for Hepatocellular Carcinoma (HCC) in cirrhotic patients. Data was collected from main medical databases up to August 2016, to identify eligible studies assessing cost-effectiveness of HCC surveillance in cirrhotic patients. The included studies were reviewed to extract information on study design, surveillance strategies, model parameters, data sources of model variables, and results of base case analysis. Base case Incremental Cost-Effectiveness Ratio (ICER) per life year was adjusted to the 2015 currency value and presented as a ratio to the 2015 Gross Domestic Product (GDP) per capita for comparisons across countries. Simple linear regression analyses were performed to assess the impact of model variables on adjusted ICER per Quality Adjusted Life Year (QALY). Twelve studies from 8 countries were identified. When compared to no surveillance, the ICERs per life year associated with image-based surveillance were ranked by semi-annual Ultrasound (US) (0.16 GDP per capita), semiannual contrast-enhanced US (0.17 GDP per capita), annual US plus Alpha-Fetoprotein (AFP) (0.54 GDP per capita), semi-annual computed tomography plus AFP (0.60 GDP per capita), and semi-annual US plus AFP (0.63 GDP per capital). Semi-annual surveillance (coefficient 1.919, P=0.002) and annual mortality of decompensated cirrhosis (coefficient 13.762, P<0.001) were significantly associated with increased ICERs per QALY for image-based surveillance. Semi-annual US was likely the most costeffective image-based surveillance for HCC in cirrhotic patients. The cost-effectiveness of HCC surveillance was highly sensitive to surveillance frequency and mortality of decompensated cirrhosis.

Author(s): Zhengping Xiong, Fang Huang
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