The microbiome plays a crucial role in integrating environmental influences into host physiology, potentially linking it to autoimmune liver diseases, such as autoimmune hepatitis, primary biliary cholangitis, and primary sclerosing cholangitis. All autoimmune liver diseases are associated with reduced diversity of the gut microbiome and altered abundance of certain bacteria. However, the relationship between the microbiome and liver diseases is bidirectional and varies over the course of the disease. This makes it challenging to dissect whether such changes in the microbiome are initiating or driving factors in autoimmune liver diseases, secondary consequences of disease and/or pharmacological intervention, or alterations that modify the clinical course that patients experience. Potential mechanisms include the presence of pathobionts, disease-modifying microbial metabolites, and more nonspecific reduced gut barrier function, and it is highly likely that the effect of these change during the progression of the disease. Recurrent disease after liver transplantation is a major clinical challenge and a common denominator in these conditions, which could also represent a window to disease mechanisms of the gut-liver axis. Herein, we propose future research priorities, which should involve clinical trials, extensive molecular phenotyping at high resolution, and experimental studies in model systems. Overall, autoimmune liver diseases are characterized by an altered microbiome, and interventions targeting these changes hold promise for improving clinical care based on the emerging field of microbiota medicine.
Background and aims: Systemic treatments are listed as first-line therapies for HCC with portal vein tumor thrombus (PVTT), resulting in modest efficacy. We aimed to evaluate the efficacy and safety of sintilimab plus bevacizumab combined with radiotherapy in HCC with PVTT and to identify prognostic biomarkers.
Approach and results: This open-label, multicenter, single-arm, phase 2 clinical trial was conducted at 3 tertiary hospitals in China. A total of 46 patients with HCC with PVTT were enrolled. All the patients received the first cycle of i.v. sintilimab (200 mg, day 1) plus bevacizumab (15 mg/kg, day 1) within 3 days after enrollment. Radiotherapy (30-50 Gy/10 fractions) was administered after 2 cycles of Sin-Bev. Sin-Bev was disrupted during radiotherapy and resumed 2 weeks after radiotherapy and continued every 3 weeks thereafter until disease progression, unacceptable toxicity, or withdrawal of consent. The primary end point was objective response rate. Patients obtained an objective response rate of 58.7% and a disease control rate of 100%. After a median follow-up time of 26.0 months (95% CI: 24.0-26.0), the median OS was 24.0 months (95% CI: 19.0 to not applicable) and the median progression-free survival was 13.8 months (95% CI: 12.0-21.0), respectively. No unexpected adverse events or treatment-related deaths occurred. Mutations of PCTMD1 were predictive of shorter OS and progression-free survival.
Conclusions: Sintilimab plus bevacizumab combined with radiotherapy provides favorable treatment response and survival outcomes along with an acceptable safety profile in the first-line setting for patients with HCC with PVTT (ClinicalTrials.gov Identifier: NCT05010434).
Background and aims: Utilization of electronic health records data to derive predictive indexes such as the electronic Child-Turcotte-Pugh (eCTP) Score can have significant utility in health care delivery. Within the records, CT scans contain phenotypic data which have significant prognostic value. However, data extractions have not traditionally been applied to imaging data. In this study, we used artificial intelligence to automate biomarker extraction from CT scans and examined the value of these features in improving risk prediction in patients with liver disease.
Approach and results: Using a regional liver disease cohort from the Veterans Health System, we retrieved administrative, laboratory, and clinical data for Veterans who had CT scans performed for any clinical indication between 2008 and 2014. Imaging biomarkers were automatically derived using the analytic morphomics platform. In all, 4614 patients were included. We found that the eCTP Score had a Concordance index of 0.64 for the prediction of overall mortality while the imaging-based model alone or with eCTP Score performed significantly better [Concordance index of 0.72 and 0.73 ( p <0.001)]. For the subset of patients without hepatic decompensation at baseline (n=4452), the Concordance index for predicting future decompensation was 0.67, 0.79, and 0.80 for eCTP Score, imaging alone, or combined, respectively.
Conclusions: This proof of concept demonstrates that the potential of utilizing automated extraction of imaging features within CT scans either alone or in conjunction with classic health data can improve risk prediction in patients with chronic liver disease.
Background and aims: The landscape in primary biliary cholangitis (PBC) has changed with the advent of second-line treatments. However, the use of obeticholic acid (OCA) and fibrates in PBC-related cirrhosis is challenging. We assessed the impact of receiving a second-line therapy as a risk factor for decompensated cirrhosis in a real-world population with cirrhosis and PBC, and identify the predictive factors for decompensated cirrhosis in these patients.
Approach and results: Multicenter study enrolling 388 patients with PBC-cirrhosis from the Spanish ColHai registry. Biopsy (20%), ultrasound (59%), or transient elastography (21%) defined cirrhosis, and the presence of varices and splenomegaly defined clinically significant portal hypertension (CSPH). Paris-II and PBC OCA international study of efficacy criteria determined the response to ursodeoxycholic acid (UDCA), fibrates (n=93), and OCA (n=104). The incidence of decompensated cirrhosis decreased for UDCA versus OCA or fibrates in the real-world population, but they were similar considering the propensity score-matched cohort (UDCA 3.77 vs. second-line therapy 4.5 100 persons-year, respectively), as patients on second-line therapy exhibited advanced liver disease. Consequently, GGT, albumin, platelets, clinically significant portal hypertension, and UDCA response were associated with a decompensating event. OCA response (achieved in 52% of patients) was associated with bilirubin (OR 0.21 [95% CI: 0.06-0.73]) and AST (OR 0.97 [95% CI: 0.95-0.99]), while fibrate response (achieved in 55% of patients) with AST [OR 0.96 (95% CI: 0.95-0.98]). In patients treated with OCA, drug response (sHR 0.23 [95% CI: 0.08-0.64]), diabetes (sHR 5.62 [95% CI: 2.02-15.68]), albumin (sHR 0.34 [95% CI: 0.13-0.89]), and platelets (sHR 0.99 [95% CI: 0.98-1.00]) were related to decompensation. In patients treated with fibrate, drug response (sHR 0.36 (95% CI: 0.14-0.95]), albumin (sHR 0.36 (95% CI: 0.16-0.81]), and clinically significant portal hypertension (sHR 3.70 (95% CI: 1.17-11.70]) were associated with decompensated cirrhosis.
Conclusions: Advanced PBC, rather than OCA and fibrates, was found to be associated with decompensating events. Therefore, biochemical and clinical variables should be considered when making decisions about the management of these drugs. Moreover, a positive response to OCA and fibrates reduced the risk of decompensation.