{"title":"Hepatocellular carcinoma risk prediction and early detection in patients with metabolic dysfunction associated steatotic liver disease.","authors":"Jeff Liang, Naomy Kim, Ju Dong Yang","doi":"10.21037/tgh-24-41","DOIUrl":null,"url":null,"abstract":"<p><p>The rising prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) and its more severe form, metabolic dysfunction-associated steatohepatitis (MASH), is closely linked with a heightened risk of hepatocellular carcinoma (HCC), the fourth leading cause of cancer-related deaths worldwide. Despite the elevated risk of HCC in patients with MASLD, the existing surveillance guidelines are inadequate, particularly for those without cirrhosis. This review evaluates current HCC surveillance practices in patients with MASLD and their shortcomings. It also highlights the critical need for enhanced HCC risk stratification and diagnostic accuracy through new techniques. In this review article, we performed a comprehensive literature review of studies focusing on HCC risk factors in MASLD/MASH patients from 2000 to 2023. We discussed that demographics, comorbidities, liver fibrosis, and genetic markers play critical roles in HCC risk stratification. Additionally, non-invasive tests (NITs) for fibrosis may improve the accuracy for HCC risk stratification and diagnosis. More recently, innovative approaches, such as machine learning techniques and liquid biopsy utilizing extracellular vesicles, cell-free DNA, and circulating tumor cells show promise in redefining early HCC detection. Thus, integrating these various risk factors could optimize early detection of HCC for the growing MASLD/MASH patient population. However, further research is needed to confirm their effectiveness and practical implementation in clinical settings.</p>","PeriodicalId":94362,"journal":{"name":"Translational gastroenterology and hepatology","volume":null,"pages":null},"PeriodicalIF":3.8000,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11535805/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Translational gastroenterology and hepatology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21037/tgh-24-41","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"GASTROENTEROLOGY & HEPATOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
The rising prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) and its more severe form, metabolic dysfunction-associated steatohepatitis (MASH), is closely linked with a heightened risk of hepatocellular carcinoma (HCC), the fourth leading cause of cancer-related deaths worldwide. Despite the elevated risk of HCC in patients with MASLD, the existing surveillance guidelines are inadequate, particularly for those without cirrhosis. This review evaluates current HCC surveillance practices in patients with MASLD and their shortcomings. It also highlights the critical need for enhanced HCC risk stratification and diagnostic accuracy through new techniques. In this review article, we performed a comprehensive literature review of studies focusing on HCC risk factors in MASLD/MASH patients from 2000 to 2023. We discussed that demographics, comorbidities, liver fibrosis, and genetic markers play critical roles in HCC risk stratification. Additionally, non-invasive tests (NITs) for fibrosis may improve the accuracy for HCC risk stratification and diagnosis. More recently, innovative approaches, such as machine learning techniques and liquid biopsy utilizing extracellular vesicles, cell-free DNA, and circulating tumor cells show promise in redefining early HCC detection. Thus, integrating these various risk factors could optimize early detection of HCC for the growing MASLD/MASH patient population. However, further research is needed to confirm their effectiveness and practical implementation in clinical settings.