Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Background/Aims: To determine the association between evolutionary changes in metabolic dysfunction-associated steatotic liver disease (MASLD) status and the risk of hepatocellular carcinoma (HCC) in a nationwide population-based cohort. Methods: Information on study participants was derived from the Korea National Health Insurance Service database. The study population consisted of 5,080,410 participants who underwent two consecutive biennial health screenings between 2009 and 2012. All participants were followed up until HCC, death, or 31 December 2020. The association of evolutionary changes in MASLD status, as assessed by the fatty liver index and cardiometabolic risk factors, including persistent non-MASLD, resolved MASLD, incident MASLD, and persistent MASLD, with HCC risk was evaluated using multivariable-adjusted Cox proportional hazards regression. Results: Among the 5,080,410 participants with 39,910,331 person-years of follow-up, 4,801 participants developed HCC. The incidence of HCC in participants with resolved, incident, and persistent MASLD was approximately 2.2-, 2.3-, and 4.7-fold higher, respectively, than that in those with persistent non-MASLD among the Korean adult population. When stratifying the participants according to the evolutionary change in MASLD status, persistent (adjusted hazard ratio [aHR], 2.94; 95% confidence interval [CI], 2.68–3.21; P<0.001), incident (aHR, 1.85; 95% CI, 1.63–2.10; P<0.001), and resolved MASLD (aHR, 1.33; 95% CI, 1.18–1.50; P<0.001) had an increased risk of HCC compared to persistent non-MASLD. Conclusions The evolutionary changes in MASLD were associated with the differential risk of HCC independent of metabolic risk factors and concomitant medications, providing additional information on the risk of HCC stratification in patients with MASLD.