Introduction: Ultrasound (US) is associated with severe visualization limitations (US Liver Imaging Reporting and Data System visualization score C) in one-third of patients with nonalcoholic fatty liver disease (NAFLD) cirrhosis undergoing hepatocellular carcinoma (HCC) screening. Data suggest abbreviated MRI (aMRI) may improve HCC screening efficacy. This study analyzed the cost-effectiveness of HCC screening strategies, including an US visualization score-based approach with aMRI, in patients with NAFLD cirrhosis.
Methods: We constructed a Markov model simulating adults with compensated NAFLD cirrhosis in the United States undergoing HCC screening, comparing strategies of US plus visualization score, US alone, or no surveillance. We modeled aMRI in patients with visualization score C and negative US, while patients with scores A/B did US alone. We performed a sensitivity analysis comparing US plus visualization score with US plus alpha fetoprotein or no surveillance. The primary outcome was the incremental cost-effectiveness ratio (ICER), with a willingness-to-pay threshold of $100,000 per quality-adjusted life-year. Sensitivity analyses were performed for all variables.
Results: US plus visualization score was the most cost-effective strategy, with an ICER of $59,005 relative to no surveillance. The ICER for US alone to US plus visualization score was $822,500. On sensitivity analysis, screening using US plus visualization score remained preferred across several parameters. Even with alpha fetoprotein added to US, the US plus visualization score strategy remained cost-effective, with an ICER of $62,799 compared with no surveillance.
Discussion: HCC surveillance using US visualization score-based approach, using aMRI for visualization score C, seems to be the most cost-effective strategy in patients with NAFLD cirrhosis.
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http://dx.doi.org/10.14309/ajg.0000000000002636 | DOI Listing |
J Perianesth Nurs
January 2025
Department of Gynecology, the First Hospital of Lanzhou University, Lanzhou, China.
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Design: Randomized controlled trial.
Methods: A randomized double-blind clinical trial was designed.
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View Article and Find Full Text PDFBMC Musculoskelet Disord
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Department of Orthopedics, Peking University Third Hospital, No. 49. North Garden Street, Hai Dian District, Beijing, 100191, People's Republic of China.
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January 2025
Department of Critical Care Medicine, West China Hospital, Sichuan University, 37 Guo Xue Xiang St, Chengdu, 610041, Sichuan, China.
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NPJ Digit Med
January 2025
Graduate School of Data Science, Seoul National University, Seoul, Republic of Korea.
Polysomnography (PSG) is crucial for diagnosing sleep disorders, but manual scoring of PSG is time-consuming and subjective, leading to high variability. While machine-learning models have improved PSG scoring, their clinical use is hindered by the 'black-box' nature. In this study, we present SleepXViT, an automatic sleep staging system using Vision Transformer (ViT) that provides intuitive, consistent explanations by mimicking human 'visual scoring'.
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