Hepatology Communications最新文献

Background and aims: Immunosuppression can cause hepatitis B virus (HBV) reactivation, leading to severe outcomes in patients with "resolved" HBV infection. This multicenter, randomized, placebo-controlled trial assessed the efficacy of preemptive antiviral therapy in HBsAg-negative, anti-HBc-positive patients receiving rituximab-based chemotherapy for non-Hodgkin lymphoma (NHL).

Methods: Patients were randomized 1:1 to tenofovir alafenamide (TAF)/placebo across 3 phases: chemotherapy plus TAF/placebo (phase 1), TAF/placebo post-chemotherapy (phase 2), and follow-up after therapy cessation (phase 3). The primary endpoint was HBsAg reverse seroconversion. HBsAg and ALT were monitored every 3-12 weeks, depending on treatment phase, and HBV DNA was measured post hoc. ClinicalTrials.gov (NCT02186574).

Results: Among 42 patients (median age 65.2 years, 52.4% male, 52.4% aggressive lymphoma, 73.8% anti-HBs positive), 20 received TAF and 22 received a placebo. Median ALT was 20.0 U/L (IQR: 15.0-28.0) at baseline. Median follow-up was 69.4 weeks (IQR: 63.7-166), with 6.1 weeks (IQR: 4.7-8.3) between visits. During follow-up, 2 patients in the TAF arm, but none receiving placebo, experienced HBsAg reverse seroconversions: occurring in phase 3 at 62.3 weeks from baseline, and in phase 1 at 20.0 weeks from baseline. Neither patient experienced ALT >2× ULN. HBV DNA >1000 IU/mL was observed in 8 instances among 6 patients, 3 in each arm, with no associated hepatitis. Low-level DNA (<1000 IU/mL) was not indicative of reverse seroconversion, DNA increases, or ALT elevations.

Conclusions: The use of preemptive TAF therapy did not reduce the risk of HBsAg reverse seroconversion; however, the findings should be interpreted with caution as the study was underpowered due to slow enrolment leading to early termination. Low-level HBV DNA elevations were not associated with HBV reactivation. Thus, close HBsAg and ALT monitoring are adequate in HBsAg-negative patients undergoing rituximab-based chemotherapy.

Background: Although ultrasonography (US) is widely recommended for HCC surveillance, its limited sensitivity for early-stage HCC remains a concern. Gadoxetic acid-enhanced abbreviated MRI (HBP-AMRI) has demonstrated high diagnostic performance; however, its role in routine surveillance settings remains uncertain due to limited prospective comparative evidence. The AMRIUS study (Abbreviated MRI using gadoxetic acid versus Ultrasonography for Surveillance of early-stage HCC in high-risk patients) aims to prospectively compare the effectiveness of HBP-AMRI and US for HCC surveillance in high-risk patients with cirrhosis.

Methods: AMRIUS is a randomized controlled trial (RCT) enrolling 806 high-risk patients with cirrhosis, randomly assigned (1:1) to undergo either biannual HBP-AMRI or US for 2 surveillance rounds. The primary endpoint is the detection rate of early-stage HCC [Barcelona Clinic Liver Cancer (BCLC) stage 0 or A]. Secondary endpoints include false referral rate of BCLC 0 or A HCC, detection and false referral rates for BCLC stage 0 and all-stage HCC, BCLC stage distribution at initial HCC diagnosis, and the rate of curative treatment. Structured imaging protocols and quality assessments will be implemented.

Discussion: AMRIUS is the first RCT designed to provide high-level evidence comparing HBP-AMRI and US for HCC surveillance. Its findings are expected to inform future guidelines and support risk-adapted strategies that prioritize early detection and curative treatment eligibility, particularly for patients likely to benefit from high-sensitivity imaging.

Trial registration: Registered at Clinical Research Information Service on May 22, 2022 (KCT0007417) and ClinicalTrials.gov on March 9, 2024 (NCT06312826). Participant recruitment began on August 26, 2022. Follow-up is ongoing.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common chronic liver disease and is estimated to affect over a billion people worldwide. MASLD patients may progress to more severe forms, including metabolic dysfunction-associated steatohepatitis (MASH) and hepatocellular carcinoma (HCC) with or without cirrhosis. Recent data demonstrated that HCC represents the fifth most common cancer and is the second leading cause of cancer-related death globally, and MASLD has been recognized as a rapidly emerging cause for this malignancy. Given that, diagnosis at the early stage and assessing the risks of progression to HCC are critically important for MASLD patients. However, the optimal screening strategies for patients with MASLD at risk of cancer are still under debate. Although various studies have shown potential for MASLD-related HCC (MASLD-HCC) treatment, the clinical therapeutics are still faced with huge challenges due to the complexity of the pathogenesis of the disease. Herein, we present an overview of the current advancements of early detection and risk evaluation for MASLD and MASLD-HCC patients, and the therapeutic approaches adopted in current clinical management.

Chronic liver disease (CLD) is a progressive condition marked by persistent inflammation and regeneration of hepatic tissue, often leading to cirrhosis and increased susceptibility to microbial infections. These infections not only trigger acute decompensation and acute-on-chronic liver failure but also contribute to poor clinical outcomes despite antibiotic treatment. Conversely, CLD itself exacerbates infection severity, forming a vicious cycle. Recent research has highlighted the diverse and coordinated roles of liver parenchymal and nonparenchymal cells in antimicrobial immunity. Hepatocytes control infection by producing a large number of antimicrobial peptides, opsonins, and inflammatory mediators. KCs are key to capturing and clearing blood-borne pathogens and orchestrating immune responses. LSECs facilitate immune cell trafficking, pathogen sensing, and modulation of neutrophil-mediated defense. HSCs are activated during bacterial infections and promote fibrosis through inflammasome and TGF-β signaling. Biliary epithelial cells serve as frontline defenders in the biliary tract, expressing pattern recognition receptors and secreting cytokines, chemokines, defensins, and IgA. Understanding the complex interplay between hepatocytes, liver nonparenchymal cells, and immune components is crucial for developing targeted therapies to improve infection control and outcomes in patients with chronic liver disease. Here, we provide a comprehensive summary of the roles played by different hepatic cell types during microbial infections with a focus on bacterial infection. The potential mechanisms underlying the increased susceptibility of CLDs to these infections are also briefly discussed.

Background: Although medical risk prediction tools are widely developed, few achieve sustained clinical adoption. In cirrhosis patients, surgical risk calculators have achieved broad utilization. We sought to identify key design and implementation factors that influence provider uptake of such tools, using the VOCAL-Penn score (VPS) as a case example.

Methods: We conducted a qualitative study of 22 diverse clinicians who care for patients with cirrhosis. Semi-structured interviews were guided by the Consolidated Framework for Implementation Research to explore factors influencing the adoption of risk prediction tools. Interviews were transcribed and analyzed using a combined grounded theory and deductive approach. Emergent themes were synthesized into a conceptual framework.

Results: Five recurrent themes emerged as central: efficiency, accessibility, transparency, accuracy, and generalizability. Clinicians emphasized the need for tools that are intuitive, require minimal inputs, and integrate seamlessly into existing workflows. Ensuring input variables were clinically meaningful and readily available was cited as critical to encouraging use. Transparency in model development was essential to building trust. Participants stressed the importance of comparative performance data relative to existing clinical standards, as well as published external validations, to support the tool's credibility. Finally, generalizability was key to equitable application across diverse patient populations.

Conclusions: Using the VPS as a grounding example, our findings identify 5 domains-efficiency, accessibility, transparency, accuracy, and generalizability-that inform the development and dissemination of future tools. By aligning tool design with real-world clinical needs, this framework may support broader adoption and more equitable implementation of medical risk prediction tools.

Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) affects ~30% of the US adult population, and its prevalence is increasing. Early-stage disease is often missed by clinicians as it is largely asymptomatic until cirrhosis develops. Recent advances in artificial intelligence (AI) have allowed for expanded electronic health record (EHR) identification of several diseases. We aimed to develop an algorithm that utilizes AI to identify patients with MASLD via a large-scale review within the EHR.

Methods: We created a natural language processing (NLP) algorithm that identifies patients with hepatic steatosis on abdominal imaging and selects for patients meeting MASLD criteria. Validation was carried out via manual review of monthly generated cohorts. The algorithm was then utilized to retrieve a MASLD cohort for initial analysis. Demographics were summarized, and additional variables pertaining to early MASLD management were analyzed.

Results: Our algorithm identified patients with MASLD with a positive predictive value (PPV) of over 93%. The NLP component of the algorithm identified hepatic steatosis in imaging reports with a PPV of up to 99.4% and excluded patients with alcohol use with a negative predictive value of ~95%. From a cohort spanning 6 months, 957 individuals with MASLD were identified by the algorithm, of which 14.6% (n=140) had a MASLD-related diagnosis code.

Conclusions: We developed an AI algorithm that can perform a large-scale review of electronic health records to identify patients with MASLD with >93% accuracy. Our initial analysis suggests that a substantial proportion of individuals meeting MASLD criteria do not yet carry a MASLD-related diagnosis. Our work can be adapted by other institutions to enhance the detection of MASLD and alcohol use patterns, allowing for targeted interventions to prevent disease progression and improve outcomes.