Clinical and Molecular Hepatology最新文献

Background and aims: Various expanded criteria (EC) for liver transplantation (LT) in patients with hepatocellular carcinoma (HCC) have been proposed to avoid the narrow nature of the Milan criteria (MC). To investigate which EC predicts more favorable outcomes in terms of overall survival (OS) and recurrence-free survival (RFS), we conducted a network meta-analysis (NMA).

Methods: A database search was conducted on PubMed, Embase, and the Cochrane Library, to identify studies comparing OS and RFS between patients within the MC and those exceeding the MC but within the EC. Effect sizes were assessed using hazard ratios (HR), which were pooled in a random-effects NMA. The NMA results were validated in an in-house cohort of 1,008 LT recipients.

Results: Of 22,466 articles identified, 35 studies contained 45 pairwise comparisons and were included in the NMA along with 8 different EC. The use of UCSF (HR, 1.43; 95% CI, 1.19-1.71), Up-to-Seven (HR, 1.50; 95% CI, 1.15-1.97), and Hangzhou criteria (HR, 1.69; 95% CI, 1.11-2.57) yielded OS results inferior to the MC. The MC had the highest rank probability of being best followed by Metroticket 2.0 model and Asan criteria in terms of OS and RFS, respectively. Both Metroticket 2.0 and AFP model yielded more favorable HCC-specific mortality than other EC in the validation cohort.

Conclusion: Several EC, of which those of Metroticket 2.0 model were the best, yielded comparable outcomes to the MC. AFP-based EC such as Metroticket 2.0 and AFP model appeared to be useful in both the NMA and the validation cohort, suggesting a potential role in identifying selected low-risk patients beyond the MC.

Hepatocellular carcinoma (HCC) imposes a major health and economic burden worldwide, with disproportionate effects in low- and middle-income countries (LMICs). Surveillance in high-risk populations, typically using semiannual ultrasound and alpha-fetoprotein (AFP) testing, has been shown to be cost-effective by enabling earlier detection and improving survival. Yet, its overall value is reduced by poor adherence and the limited sensitivity of ultrasound, particularly in patients with metabolic-associated steatotic liver disease. Emerging approaches-including abbreviated MRI, multi-biomarker models (e.g., GALAD), and liquid biopsy assays such as methylated DNA markers-demonstrate greater diagnostic accuracy and potential economic advantages compared with conventional methods. Integration of artificial intelligence (AI) into imaging may further enhance efficiency and reduce downstream costs. Moving toward precision surveillance, guided by individualized risk stratification that incorporates etiology, fibrosis stage, and molecular profiles, can optimize allocation of resources and maximize cost-effectiveness at the population level. Interventions to improve adherence, including mailed outreach and behavioral economic incentives, have shown both clinical benefit and cost savings, underscoring the role of implementation science. Because socioeconomic disparities influence both access and outcomes, economic models must explicitly address equity to achieve sustainable impact. Future research should prioritize prospective trials that evaluate not only clinical performance but also the real-world cost-effectiveness of novel technologies and stratified surveillance strategies. For LMICs, adapting proven models into affordable, context-appropriate programs is essential. By combining prevention, precision risk assessment, innovative technologies, and equitable implementation, HCC surveillance can deliver both clinical and economic value, reducing the global burden of disease.

Liver cancer is one of the deadliest malignancies, with increasing incidence worldwide. Recent advances in immunotherapy have expanded the options for systemic therapy against advanced hepatocellular carcinoma (HCC), but there are no biomarkers currently available to predict which patients will respond, leading to suboptimal patient selection strategies. Understanding of the genetic and immunologic features of HCC is accelerating rapidly through the use of single cell and spatial transcriptomic techniques. However, there is a need to translate insights gained through these new studies to improve treatment options and improve patient selection. In this review we summarize knowledge of the immunogenomics of HCC, emphasizing recent advances, and discuss progress toward clinical translation.

Background/aims: Patients with concurrent type 2 diabetes mellitus (T2DM) and metabolic dysfunction-associated steatotic liver disease (MASLD) face elevated cardiovascular risks. However, optimal oral antidiabetic drug (OAD) selection for this population remains unclear.

Methods: Using the Korean National Health Information Database, we conducted a target trial emulation comparing cardiovascular outcomes among patients with T2DM and MASLD (defined by fatty liver index ≥30) who initiated sodium-glucose cotransporter 2 (SGLT2) inhibitors, thiazolidinediones, dipeptidyl peptidase-4 (DPP-4) inhibitors, or sulfonylureas with metformin. The primary outcome was major adverse cardiovascular events (MACE), including cardiovascular mortality, nonfatal myocardial infarction, and nonfatal stroke.

Results: Among 71,071 patients (331,726 person-years), SGLT2 inhibitor users experienced a significantly lower MACE risk compared to sulfonylurea users (adjusted subdistribution hazard ratio [aSHR], 0.44; 95% CI, 0.31-0.62). SGLT2 inhibitors also demonstrated a lower MACE risk compared to thiazolidinediones (aSHR, 0.61; 95% CI, 0.39-0.96) and DPP-4 inhibitors (aSHR, 0.59; 95% CI, 0.42-0.96). Cardiovascular mortality risk was notably reduced with SGLT2 inhibitors compared to sulfonylureas (aSHR, 0.13; 95% CI, 0.03-0.50), thiazolidinediones (aSHR, 0.19; 95% CI, 0.04-0.86), and DPP-4 inhibitors (aSHR, 0.22; 95% CI, 0.06-0.84). Mediation analysis revealed that MASLD regression accounted for 8.7% of the total cardiovascular benefit when comparing SGLT2 inhibitors to sulfonylureas.

Conclusions: In patients with concurrent T2DM and MASLD, SGLT2 inhibitors demonstrated better cardiovascular outcomes compared to other OADs. These findings suggest that SGLT2 inhibitors may be the preferred OAD choice for cardiovascular risk reduction in this high-risk population.