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SWOT analysis of noninvasive tests for diagnosing NAFLD with severe fibrosis: an expert review by the JANIT Forum

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JOURNAL OF GASTROENTEROLOGY
卷 58, 期 2, 页码 79-97

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SPRINGER JAPAN KK
DOI: 10.1007/s00535-022-01932-1

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NAFLD/NASH; Scoring system; Biomarker; Elastography; Artificial intelligence

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Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease, which can progress to nonalcoholic steatohepatitis (NASH), liver cirrhosis, and hepatocellular carcinoma (HCC). Liver fibrosis degree is now considered a prognostic factor for NAFLD/NASH. However, the invasive and costly nature of liver biopsy, as well as the inter-observer diagnosis variability, poses challenges. To address these issues, various noninvasive tests (NITs) including blood biomarkers and imaging methods have been developed for NAFLD assessment. The Japan NASH NIT (JANIT) Forum aims to promote the development of NITs for assessing disease severity and treatment response through multi-stakeholder dialogue and open innovation.
Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease. Nonalcoholic steatohepatitis (NASH) is an advanced form of NAFLD can progress to liver cirrhosis and hepatocellular carcinoma (HCC). Recently, the prognosis of NAFLD/NASH has been reported to be dependent on liver fibrosis degree. Liver biopsy remains the gold standard, but it has several issues that must be addressed, including its invasiveness, cost, and inter-observer diagnosis variability. To solve these issues, a variety of noninvasive tests (NITs) have been in development for the assessment of NAFLD progression, including blood biomarkers and imaging methods, although the use of NITs varies around the world. The aim of the Japan NASH NIT (JANIT) Forum organized in 2020 is to advance the development of various NITs to assess disease severity and/or response to treatment in NAFLD patients from a scientific perspective through multi-stakeholder dialogue with open innovation, including clinicians with expertise in NAFLD/NASH, companies that develop medical devices and biomarkers, and professionals in the pharmaceutical industry. In addition to conventional NITs, artificial intelligence will soon be deployed in many areas of the NAFLD landscape. To discuss the characteristics of each NIT, we conducted a SWOT (strengths, weaknesses, opportunities, and threats) analysis in this study with the 36 JANIT Forum members (16 physicians and 20 company representatives). Based on this SWOT analysis, the JANIT Forum identified currently available NITs able to accurately select NAFLD patients at high risk of NASH for HCC surveillance/therapeutic intervention and evaluate the effectiveness of therapeutic interventions.

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