Annals of hepatology最新文献

Recent efforts to reclassify non-alcoholic fatty liver disease (NAFLD) as metabolic dysfunction-associated fatty liver disease (MAFLD) and metabolic dysfunction-associated steatotic liver disease (MASLD) are intended to divert attention to the metabolic basis of the disease rather than to alcohol consumption. This reclassification recognizes the role of obesity, sedentary lifestyles and poor dietary habits in the development of the disease, leading to a better understanding of its etiology. Nevertheless, the transition has posed its own challenges, particularly with regard to communication between patient and healthcare professional. Many healthcare professionals report difficulty in explaining the nuanced concepts, especially the term "steatosis". In addition, the change in terminology has not yet removed the stigma, with ongoing debates about the appropriateness of the terms "fatty" and "steatotic". Surveys suggest that while "obesity" may be perceived as more stigmatizing, the medical term "steatotic liver disease" is not considered as stigmatizing, indicating a disconnect in perceptions between healthcare professionals and patients.

Introduction and Objectives

Autoimmune liver diseases (AILD) are rare causes hepatocellular carcinoma (HCC), and data on the efficacy and tolerability of anti-tumor therapies are scarce. This pan-European study aimed to assess outcomes in AILD-HCC patients treated with tyrosine kinase inhibitors (TKIs) or transarterial chemoembolization (TACE) compared with patients with more common HCC etiologies, including viral, alcoholic or non-alcoholic fatty liver disease.

Materials and Methods

107 patients with HCC-AILD (AIH:55; PBC:52) treated at 13 European centres between 1996 and 2020 were included. 65 received TACE and 28 received TKI therapy. 43 (66 %) were female (median age 73 years) with HCC tumor stage BCLC A (34 %), B (46 %), C (9 %) or D (11 %). For each treatment type, propensity score matching was used to match AILD to non-AILD-HCC on a 1:1 basis, yielding in a final cohort of 130 TACE and 56 TKI patients for comparative analyses of median overall survival (mOS) and treatment tolerability.

Results

HCC-AILD patients showed comparable mOS to controls for both TACE (19.5 vs. 22.1 months, p = 0.9) and TKI (15.4 vs. 15.1 months, p = 0.5). Adverse events were less frequent in AILD-HCC patients than controls (33 % % vs. 62 %, p = 0.003). For TKIs, there were no significant differences in adverse events (73% vs. 86%, p = 0.2) or interruption rates (44% vs. 36 %, p = 0.7).

Conclusions

In summary, this study demonstrates comparable mOS for AILD-HCC patients undergoing local and systemic treatments, with better tolerability than HCC of other causes. TKIs remain important therapeutic options for AILD-HCC patients, particularly given their exclusion from recent immunotherapy trials.

Introduction and Objectives

Autoimmune liver diseases (AILDs) are rare and require precise evaluation, which is often challenging for medical providers. Chatbots are innovative solutions to assist healthcare professionals in clinical management. In our study, ten liver specialists systematically evaluated four chatbots to determine their utility as clinical decision support tools in the field of AILDs.

Materials and Methods

We constructed a 56-question questionnaire focusing on AILD evaluation, diagnosis, and management of Autoimmune Hepatitis (AIH), Primary Biliary Cholangitis (PBC), and Primary Sclerosing Cholangitis (PSC). Four chatbots -ChatGPT 3.5, Claude, Microsoft Copilot, and Google Bard- were presented with the questions in their free tiers in December 2023. Responses underwent critical evaluation by ten liver specialists using a standardized 1 to 10 Likert scale. The analysis included mean scores, the number of highest-rated replies, and the identification of common shortcomings in chatbots performance.

Results

Among the assessed chatbots, specialists rated Claude highest with a mean score of 7.37 (SD = 1.91), followed by ChatGPT (7.17, SD = 1.89), Microsoft Copilot (6.63, SD = 2.10), and Google Bard (6.52, SD = 2.27). Claude also excelled with 27 best-rated replies, outperforming ChatGPT (20), while Microsoft Copilot and Google Bard lagged with only 6 and 9, respectively. Common deficiencies included listing details over specific advice, limited dosing options, inaccuracies for pregnant patients, insufficient recent data, over-reliance on CT and MRI imaging, and inadequate discussion regarding off-label use and fibrates in PBC treatment. Notably, internet access for Microsoft Copilot and Google Bard did not enhance precision compared to pre-trained models.

Conclusions

Chatbots hold promise in AILD support, but our study underscores key areas for improvement. Refinement is needed in providing specific advice, accuracy, and focused up-to-date information. Addressing these shortcomings is essential for enhancing the utility of chatbots in AILD management, guiding future development, and ensuring their effectiveness as clinical decision-support tools.

Introduction and Objectives

The most widely used staging system for hepatocellular carcinoma (HCC) is the Barcelona Liver Clinic Cancer (BCLC) system, which considers tumor burden, performance status, and liver function. Tumor burden is assessed with cross sectional imaging of the abdomen and chest, controversy surrounds the routine use of bone scintigraphy (BS) for detecting extrahepatic metastases. This study evaluated the role of BS in staging HCC in Mexican patients.

Patients and Methods

Retrospective cross-sectional study of all adults with HCC at a Mexican referral center from 2000 to 2018. Staging included abdominal computed tomography (CT) or magnetic resonance imaging, chest CT, and BS. The main outcome was the impact of BS on staging and/or therapy plans.

Results

Among 238 patients, 2 with fibrolamellar variant and 44 with incomplete data were excluded. Median age was 66 years, 84 % had cirrhosis, and the predominant etiology was hepatitis C virus (43 %). BCLC stages were distributed as follows: A (14 %), B (7 %), C (68 %), and D (11 %). Extrahepatic disease was present in 18 %; only 8 % patients had a positive BS. Among the positive cases, 4 were true positives, but they did not alter staging or therapy plans.

Conclusions

Routine BS in HCC staging demonstrated low yield, with a notable rate of false positives. Considering the implications of extrahepatic disease, BS may be justified for liver transplant candidates outside conventional criteria. Our study highlights the limited role of BS in early-stage HCC and advocates for a more selective utilization.

Introduction and Objectives

The absence of melanoma 2 (AIM2) protein triggers the activation of the inflammasome cascade. It is unclear whether AIM2 plays a role in hepatocellular carcinoma (HCC) and radiofrequency ablation (RFA), which uses radiofrequency waves to treat tumors. In this study, we investigated if RFA could induce pyroptosis, also called cell inflammatory necrosis, in HCC through AIM2-inflammasome signaling in vivo and in vitro.

Materials and Methods

BALB/c nude mice were used to generate HepG2 or SMMC-7721 cell-derived tumor xenografts. HCC cells with knockdown or overexpression of AIM2 were created using short hairpin RNA (shRNA) and expression vector transfection, respectively, for functional and mechanistic studies. Downstream effects were examined using flow cytometry, qRT-PCR, ELISAs, and other molecular assays.

Results

RFA significantly suppressed tumor growth in HCC cell xenografts. Flow cytometry analysis revealed that RFA could induce pyroptosis. Furthermore, AIM2, NLRP3, caspase-1, γ-H2AX, and DNA-PKc had significantly greater expression levels in liver tissues from mice treated with RFA compared with those of the controls. Additionally, interleukin (IL)-1β and IL-18 expression levels were significantly higher in the HCC cell-derived xenograft mice treated with RFA compared with those without RFA. Notably, a significantly greater effect was achieved in the RFA complete ablation group versus the partial ablation group. Knockdown or overexpression of AIM2 in HCC cells demonstrated that AIM2 exerted a role in RFA-induced pyroptosis.

Conclusions

RFA can suppress HCC tumor growth by inducing pyroptosis via AIM2. Therefore, therapeutically intervening with AIM2-mediated inflammasome signaling may help improve RFA treatment outcomes for HCC patients.

Introduction and Objectives

There are different situations in which an extrahepatic bile duct replacement or substitute is needed, such as initial and localized stages of bile duct cancer, agenesis, stenosis, or bile duct disruption.

Materials and Methods

A prosthesis obtained by electrospinning composed of Poly (D,L-lactide-co-glycolide) (PGLA) - Polycaprolactone (PCL) - Gelatin (Gel) was developed, mechanical and biological tests were carried out to evaluate resistance to tension, biocompatibility, biodegradability, cytotoxicity, morphological analysis and cell culture. The obtained prosthesis was placed in the extrahepatic bile duct of 15 pigs with a 2-year follow-up. Liver function tests and cholangioscopy were evaluated during follow-up.

Results

Mechanical and biological evaluations indicate that this scaffold is biocompatible and biodegradable. The prosthesis implanted in the experimental model allowed cell adhesion, migration, and proliferation, maintaining bile duct permeability without altering liver function tests. Immunohistochemical analysis indicates the presence of biliary epithelium.

Conclusions

A tubular scaffold composed of electrospun PGLA-PCL-Gel nanofibers was used for the first time to replace the extrahepatic bile duct in pigs. Mechanical and biological evaluations indicate that this scaffold is biocompatible and biodegradable, making it an excellent candidate for use in bile ducts and potentially in other tissue engineering applications.

Introduction and Objectives

Although the Psychometric Hepatic Encephalopathy Score (PHES) remains the gold standard in diagnosing minimal hepatic encephalopathy (MHE), its complexity limits its application in clinical practice. While more convenient tests, such as the Stroop test, Quickstroop, and the 1-min animal naming test (ANT-1), have emerged, they haven't been validated in our setting. Our objective was to validate these tests in our population.

Patients and Methods

This multicenter, observational, descriptive, and cross-sectional study was conducted in three hospitals in northeastern Mexico. MHE was defined as a PHES <-4. We included patients with cirrhosis aged >15 years without a history of overt hepatic encephalopathy. Data regarding sex, age, education, Child-Pugh/MELD-Na scores, etiology of cirrhosis, diabetes, hypertension, obesity, ascites, and clinically significant portal hypertension was collected. Fisher's exact test, Mann-Whitney U test, and receiver operating characteristic (ROC) curves were used for statistical analysis.

Results

Of the 121 patients included, 35.5 % were diagnosed with MHE. The presence of MHE was significantly associated with education level, years of study, and scores in the Stroop test, Quickstroop, and ANT-1. The AUROC curves were 77.9 %, 74.6 %, and 72.7 % for the Stroop test, Quickstroop, and ANT-1, respectively. The resulting cut-off points were 218.398 (sensitivity: 74 %; specificity: 74 %), 40.535 (sensitivity: 77 %; specificity: 68 %), and <16 animals (sensitivity: 58 %; specificity: 79 %), respectively.

Conclusions

These tests are valid diagnostic tools for detecting MHE in our population. Their simpler use and applicability could increase the early diagnosis of MHE and prompt primary prophylaxis initiation for overt hepatic encephalopathy.

Introduction and Objectives

Although unlimited sessions of conventional transarterial chemoembolization (cTACE) may be performed for liver metastases, there is no data indicating when treatment becomes ineffective. This study aimed to determine the optimal number of repeat cTACE sessions for nonresponding patients before abandoning cTACE in patients with liver metastases.

Materials and Methods

In this retrospective, single-institutional analysis, patients with liver metastases from neuroendocrine tumors (NET), colorectal carcinoma (CRC), and lung cancer who underwent consecutive cTACE sessions from 2001 to 2015 were studied. Quantitative European Association for Study of the Liver (qEASL) criteria were utilized for response assessment. The association between the number of cTACE and 2-year, 5-year, and overall survival was evaluated to estimate the optimal number of cTACE for each survival outcome.

Results

Eighty-five patients underwent a total of 186 cTACE sessions for 117 liver metastases, of which 30.7 % responded to the first cTACE. For the target lesions that did not respond to the first, second, and third cTACE sessions, response rates after the second, third, and fourth cTACE sessions were 33.3 %, 23 %, and 25 %, respectively. The fourth cTACE session was the optimal number for 2-year survival (HR 0.40; 95 %CI: 0.16–0.97; p = 0.04), 5-year survival (HR 0.31; 95 %CI: 0.11–0.87; p = 0.02), and overall survival (HR 0.35; 95 %CI: 0.13–0.89; p = 0.02).

Conclusions

Repeat cTACE in the management of liver metastases from NET, CRC, and lung cancer was associated with improved patient survival. We recommend at least four cTACE sessions before switching to another treatment for nonresponding metastatic liver lesions.

Introduction and Objectives

Despite the huge clinical burden of MASLD, validated tools for early risk stratification are lacking, and heterogeneous disease expression and a highly variable rate of progression to clinical outcomes result in prognostic uncertainty. We aimed to investigate longitudinal electronic health record-based outcome prediction in MASLD using a state-of-the-art machine learning model.

Patients and Methods

n = 940 patients with histologically-defined MASLD were used to develop a deep-learning model for all-cause mortality prediction. Patient timelines, spanning 12 years, were fully-annotated with demographic/clinical characteristics, ICD-9 and -10 codes, blood test results, prescribing data, and secondary care activity. A Transformer neural network (TNN) was trained to output concomitant probabilities of 12-, 24-, and 36-month all-cause mortality. In-sample performance was assessed using 5-fold cross-validation. Out-of-sample performance was assessed in an independent set of n = 528 MASLD patients.

Results

In-sample model performance achieved AUROC curve 0.74–0.90 (95 % CI: 0.72–0.94), sensitivity 64 %-82 %, specificity 75 %–92 % and Positive Predictive Value (PPV) 94 %-98 %. Out-of-sample model validation had AUROC 0.70–0.86 (95 % CI: 0.67–0.90), sensitivity 69 %–70 %, specificity 96 %–97 % and PPV 75 %–77 %. Key predictive factors, identified using coefficients of determination, were age, presence of type 2 diabetes, and history of hospital admissions with length of stay >14 days.

Conclusions

A TNN, applied to routinely-collected longitudinal electronic health records, achieved good performance in prediction of 12-, 24-, and 36-month all-cause mortality in patients with MASLD. Extrapolation of our technique to population-level data will enable scalable and accurate risk stratification to identify people most likely to benefit from anticipatory health care and personalized interventions.