Sarcopenia and myosteatosis are common in patients with cirrhosis. This study aimed to determine the prevalence of these muscle changes, their interrelations and their prognostic impact over a 12-month period. We conducted a prospective multicentre study involving 433 patients. Sarcopenia and myosteatosis were evaluated using computed tomography scans. The 1-year cumulative incidence of relevant events was assessed by competing risk analysis. We used a Fine-Gray model adjusted for known prognostic factors, to evaluate the impact of sarcopenia and myosteatosis on mortality, hospitalization, and liver decompensation. At enrolment, 166 patients presented with isolated myosteatosis, 36 with isolated sarcopenia, 135 with combined sarcopenia and myosteatosis and 96 patients showed no muscle changes. The 1-year cumulative incidence of death in patients with either sarcopenia and myosteatosis (13.8%) or isolated myosteatosis (13.4%) was over twice that of patients without muscle changes (5.2%) or with isolated sarcopenia (5.6%). The adjusted subhazard ratio for death in patients with muscle changes was 1.36 (95% CI 0.99, 1.86) (P=0.058). The cumulative incidence of hospitalization was significantly higher in patients with combined sarcopenia and myosteatosis than in patients without muscle changes (adjusted subhazard ratio 1.18, 95% CI 1.04 to 1.35). The cumulative incidence of liver decompensation was greater in patients with combined sarcopenia and myosteatosis (p=0.018) and those with isolated sarcopenia (p=0.046) than in patients without muscle changes. Lastly, we found a strong correlation between function tests and frailty scores with the presence of muscle changes. Myosteatosis, whether alone or combined with sarcopenia, is highly prevalent in patients with cirrhosis and is associated with significantly worse outcomes. The prognostic role of sarcopenia should always be evaluated in relation to the presence of myosteatosis. This study investigates the prognostic role of muscle changes in patients with liver cirrhosis. The novelty of this study is the multicentre, prospective nature and the distinguishing impact of individual muscle changes and their combination on prognosis in cirrhosis. This study highlights the prognostic role of myosteatosis, especially when combined with sarcopenia. On the other hand, the relevance of sarcopenia could be mitigated when considered together with myosteatosis. The implication from these findings is that sarcopenia should never be evaluated individually and that myosteatosis may have a dominant role in the prognosis of patients with liver cirrhosis.

Hepatocellular carcinoma (HCC) is the major cause of liver-related death worldwide. Interleukin 6 (IL-6) promotes the growth of the HCC microenvironment. The correlation between Child–Pugh (CP) and HCC stage and between HCC stage and sarcopenia is still not clear. Our aim was to investigate whether IL-6 is correlated with HCC stage and could represent a diagnostic marker for sarcopenia. Ninety-three HCC cirrhotic patients in different stages, according to BCLC-2022 (stages A, B, and C), were enrolled. Anthropometric and biochemical parameters, comprehensive of IL-6, were collected. The skeletal muscle index (SMI) was measured using dedicated software on computer tomography (CT) images. IL-6 level was higher in advanced (BCLC C) compared to the early-intermediate (BCLC A-B) stages (21.4 vs. 7.7 pg/mL, p < 0.005). On multivariate analysis, IL-6 levels were statistically dependent on the degree of liver disease severity (CP score) and HCC stages (p = 0.001 and p = 0.044, respectively). Sarcopenic patients presented lower BMI (24.7 ± 5.3 vs. 28.5 ± 7.0), higher PMN/lymphocyte ratio (2.9 ± 2.4 vs. 2.3 ± 1.2) and increased values of log (IL-6) (1.3 ± 0.6 vs. 1.1 ± 0.3). Univariate logistic regression between sarcopenia and log (IL-6) showed a significant odds ratio (OR 14.88, p = 0.044) with an AUC of 0.72. IL-6 appears to be an effective biomarker for the diagnosis of advanced cirrhotic HCC. In addition, IL-6 could be considered a marker of cirrhotic HCC-related sarcopenia, suggesting further investigation with BIA- or CT-dedicated software.

Background & Aims: While glucagon‐like peptide‐1 receptor agonists (GLP‐1RAs) show promise for hepatoprotection in type 2 diabetes mellitus (T2DM), the magnitude of hepatocellular carcinoma (HCC) risk reduction and optimal patient selection remain unclear. This is particularly relevant given that metabolic dysfunction‐associated steatotic liver disease (MASLD) affects 70% of patients with T2DM and represents a major HCC risk factor. We conducted a comprehensive meta‐analysis to quantify GLP‐1RA efficacy in HCC prevention and inform clinical implementation strategies. Methods: We systematically searched PubMed, Embase, and Web of Science through June 2025 for cohort studies comparing HCC incidence between GLP‐1RA users and nonusers with T2DM. Random‐effects meta‐analysis, network meta‐analysis, and meta‐regression were performed. Heterogeneity was explored through stratified analyses and quantitative bias assessment. Results: Nine studies encompassing 2,283,835 total patients (analyzed cohorts: 1,012,482) were included. GLP‐1RA use was associated with a 42% reduced HCC risk (pooled HR 0.60, 95% CI: 0.41–0.88; I ² = 86.2%). Effect magnitude varied significantly by comparator: versus insulin (HR 0.29, 95% CI: 0.13–0.67), versus oral agents (HR 0.81, 95% CI: 0.63–1.05), versus no treatment (HR 0.77, 95% CI: 0.52–1.14). Meta‐regression identified insulin as comparator as the primary driver of heterogeneity, explaining 55% of the between‐study variance. Benefits were greatest in patients without cirrhosis (HR 0.41, 95% CI: 0.29–0.58). Network meta‐analysis ranked GLP‐1RAs highest for HCC prevention (SUCRA 0.89), with insulin ranking lowest (0.08). The number needed to treat ranged from 24 to 476. Conclusions: GLP‐1RAs substantially reduce HCC risk in T2DM, with benefits partly attributable to avoiding insulin's potential hepatotoxicity. These findings support the preferential use of GLP‐1RAs over insulin in patients at HCC risk.

Combination immune checkpoint inhibitors are recommended as first-line therapy for advanced hepatocellular carcinoma. However, only a third of patients respond to treatment, and improved approaches to predict response are required. Using baseline clinical data, we aimed to use advanced machine learning models to predict overall survival and progression-free survival in patients with advanced hepatocellular carcinoma receiving atezolizumab plus bevacizumab. This retrospective cohort study was conducted at 24 centres across eight countries. Patients aged 18 years and older with a histological or radiological diagnosis of advanced hepatocellular carcinoma were included; those who had received previous systemic therapy for hepatocellular carcinoma were excluded. All patients received intravenous atezolizumab 1200 mg plus bevacizumab 15 mg/kg once every 3 weeks until disease progression. Seven supervised machine learning models, in combination with 13 feature selection techniques, were trained on 44 baseline clinical variables for the prediction of overall survival and progression-free survival. The three best-performing models, combined with their optimum feature selection techniques, were used to develop ensemble machine learning models for the prediction of overall survival and progression-free survival. The primary outcomes of the study were the predictions of overall survival, progression-free survival, and immunotherapy response using advanced machine learning. k-means clustering was used to stratify patients into two groups: those at low risk and those at high risk of either death (in the overall survival model) or disease progression (in the progression-free survival model). 934 patients who received immunotherapy from May 1, 2018 and were followed up until Oct 1, 2023 were screened, of whom 160 were excluded and 774 were included in the final study. Patients were divided into training (n=339), internal validation (n=146) and external validation (n=289) cohorts. Support vector machine, neural network, and naive Bayes algorithms had the best performance in the prediction of overall survival; for progression-free survival, the highest-performing algorithms were ridge regression, naive Bayes, and logistic regression. In the external validation cohort, the ensemble model for the prediction of overall survival (area under the receiver operating characteristic curve 0·75 [95% CI 0·69-0·81]) significantly outperformed all eight of the tested clinical benchmark variables: Barcelona Clinic Liver Cancer (BCLC) stage (0·54 [0·48-0·61]; p<0·0001), α-fetoprotein (AFP) concentration (0·60 [0·54-0·67]; p=0·0007), albumin-bilirubin (ALBI) grade (0·64 [0·58-0·71]; p=0·0003), neutrophil-to-lymphocyte ratio (0·56 [0·49-0·62]; p<0·0001), platelet-to-lymphocyte ratio (0·51 [0·44-0·58]; p<0·0001), combined ALBI grade and BCLC stage (0·67 [0·60-0·73]; p=0·0074), and two BCLC subclassifications (0·62 [0·55-0·69]; p=0·0007 and 0·61 [0·55-0·68]; p=0·0018). The ensemble model for the prediction of progression-free survival (0·64 [0·59-0·70]) outperformed five of the eight clinical predictors: BCLC stage (0·52 [0·46-0·58]; p<0·0001), neutrophil-to-lymphocyte ratio (0·53 [0·47-0·59]; p=0·0069), platelet-to-lymphocyte ratio (0·54 [0·48-0·60]; p=0·016), and two BCLC subclassifications (0·57 [0·50-0·64]; p=0·020 and 0·55 [0·49-0·62]; p=0·0091); the model did not outperform AFP concentration (0·59 [0·53-0·64]; p=0·14), ALBI grade (0·62 [0·56-0·67]; p=0·44), or combined ALBI grade and BCLC stage (0·59 [0·53-0·66]; p=0·12). For the overall survival model, patients stratified into the low-risk group had significantly longer median overall survival (16·4 months [95% CI 14·2-21·6]) than those in the high-risk group (4·8 months [3·0-6·9]; p<0·0001); similarly, patients stratified by the progression-free survival model into the low-risk group had significantly longer median progression-free survival (8·9 months [7·3-11·1]) than those in the high-risk group (3·7 months [2·9-5·6]; p=0·0021). Our advanced machine learning models, which use routinely collected baseline clinical variables, are robust and externally validated and outperform established clinical biomarkers for predicting clinical outcomes with atezolizumab plus bevacizumab. These data-driven models could be used to stratify patients with hepatocellular carcinoma for personalised treatment strategies. None.

Statins have been proposed as hepatoprotective agents in chronic liver disease (CLD); however, evidence from existing systematic reviews-including observational studies and clinical trials-is inconsistent and affected by substantial overlap. We conducted an umbrella review to synthesize the available evidence on the associations between statin use and hepatological outcomes in CLD patients, while addressing study overlap. PubMed, EMBASE, and Cochrane Library were searched up to September 2025 for systematic reviews of statin therapy in CLD. Methodological quality was evaluated using AMSTAR-2. Study overlap was assessed using corrected covered area (CCA) and minimized via hierarchical exclusion prioritizing methodological quality, comprehensiveness, and recency. Random-effects meta-analyses with bias assessments were conducted. Of 850 records screened, 17 systematic reviews (229 unique studies; 10,515,877 participants from 34 countries) were included after overlap adjustment (CCA = 5.79%). Statin therapy was associated with 46% reduction in hepatocellular carcinoma (HCC) risk (HR 0.54, 95% CI 0.48-0.59; I² = 46.7%) and 46% reduction in hepatic decompensation (HR 0.54, 95% CI 0.49-0.59; I² = 0.1%); these estimates derive predominantly from observational studies and should be interpreted as associations rather than causal effects. Geographic heterogeneity was observed: Asian populations showed stronger benefits (HCC HR 0.49, 95% CI 0.45-0.53; I² = 0%) compared with Western populations (HCC HR 0.71, 95% CI 0.52-0.96; I² = 95.7%; p = 0.003). Statin use also associated with reduced all-cause mortality (HR 0.65, 95% CI 0.52-0.81), though with substantial heterogeneity (I² = 80%). In contrast, available RCT-based evidence does not consistently confirm these associations for decompensation or mortality outcomes. Statin use is consistently associated with reduced HCC risk and hepatic decompensation in CLD patients, particularly in Asian populations, though these findings derive predominantly from observational evidence subject to potential confounding. These associations support the continued use of statins in patients with CLD and cardiovascular indications where these are otherwise indicated, with potential additive hepatoprotective effects. These results underscore the urgent need for adequately powered randomized trials to clarify the boundaries of safety and efficacy in this high-risk population.