Survival benefit from adjuvant TACE combined with Lenvatinib for patients with hepatocellular carcinoma and microvascular invasion after curative hepatectomy.

BACKGROUND AND AIMS: The prognosis of patients with hepatocellular carcinoma (HCC) undergoing hepatectomy is unsatisfactory, especially for those with microvascular invasion (MVI). This study aimed to determine the impact of adjuvant transcatheter arterial chemoembolization (TACE) and Lenvatinib on the prognosis of patients with HCC and MVI after hepatectomy. METHODS: Patients diagnosed with HCC and MVI were reviewed, and stratified into four groups according to adjuvant TACE and/or Lenvatinib. Multivariate Cox regression analyses are used to determine independent risk factors. RESULTS: 346 patients were included, and divided into four groups (Group I, TACE+ Lenvatinib; Group II, Lenvatinib; Group III, TACE; Group IV, without adjuvant therapy). Multivariable analysis showed that compared to Group IV, Group I had the best effect on improving the overall survival (OS, HR 0.321, 95%CI 0.099-0.406, P = 0.001) and recurrence-free survival (RFS, HR 0.319, 95%CI 0.129-0.372, P = 0.001). Additionally, compared with Group II or Group III, Group I also can significantly improve the OS and RFS. There is no significant difference between Group II and Group III in OS and RFS. CONCLUSION: The combination of TACE and Lenvatinib should be considered for anti-recurrence therapy for patients with HCC and MVI after hepatectomy.

Precise planning based on 3D-printed dry-laboratory models can reduce perioperative complications of laparoscopic surgery for complex hepatobiliary diseases: a preoperative cohort study.

BACKGROUND & AIMS: Complications after laparoscopic liver resection (LLR) are important factors affecting the prognosis of patients, especially for complex hepatobiliary diseases. The present study aimed to evaluate the value of a three-dimensional (3D) printed dry-laboratory model in the precise planning of LLR for complex hepatobiliary diseases. METHODS: Patients with complex hepatobiliary diseases who underwent LLR were preoperatively enrolled, and divided into two groups according to whether using a 3D-printed dry-laboratory model (3D vs. control group). Clinical variables were assessed and complications were graded by the Clavien-Dindo classification. The Comprehensive Complication Index (CCI) scores were calculated and compared for each patient. Multivariable analysis was performed to determine the risk factors of postoperative complications. RESULTS: Sixty-two patients with complex hepatobiliary diseases underwent the precise planning of LLR. Among them, thirty-one patients acquired the guidance of a 3D-printed dry-laboratory model, and others were only guided by traditional enhanced CT or MRI. The results showed no significant differences between the two groups in baseline characters. However, compared to the control group, the 3D group had a lower incidence of intraoperative blood loss, as well as postoperative 30-day and major complications, especially bile leakage (all P < 0.05). The median score on the CCI was 20.9 (range 8.7-51.8) in the control group and 8.7 (range 8.7-43.4) in the 3D group (mean difference, -12.2, P = 0.004). Multivariable analysis showed the 3D model was an independent protective factor in decreasing postoperative complications. Subgroup analysis also showed that a 3D model could decrease postoperative complications, especially for bile leakage in patients with intrahepatic cholelithiasis. CONCLUSION: The 3D-printed models can help reduce postoperative complications. The 3D-printed models should be recommended for patients with complex hepatobiliary diseases undergoing precise planning LLR.

TyG-GGT is a Reliable Non-Invasive Predictor of Advanced Liver Fibrosis in Overweight or Obese Individuals.

BACKGROUND: Liver fibrosis is a predisposing factor for liver cancer. This study will investigate the predictive role of the Triglyceride-glucose and Gamma-glutamyl transferase index (TyG-GGT) as a non-invasive indicator of advanced liver fibrosis in individuals with obesity or overweight. METHOD: We enrolled patients who underwent metabolic and bariatric surgery as well as intraoperative liver biopsies at Zhejiang provincial people's hospital from August 2020 to March 2023. Clinical characteristics, comorbidities, laboratory data, and pathological variables of patients were collected and analysed. Then, we conducted logistics regression model to compare the performance of the TyG-GGT index with other 4 non-invasive models. RESULTS: A total of 65 patients were included in this study. 43(66.2%) of them were female, with the mean body mass index (BMI) of 39.0 ± 7.3 kg/m2. Meanwhile, 24(36.9%) patients were diagnosed with diabetes. Advanced liver fibrosis were observed in 16.9% of patients, while liver cirrhosis was found in 4.6% of patients. The multivariable logistics regression showed that TyG-GGT was an independent risk factor of advanced liver fibrosis (OR = 6.989, P = 0.049). Additionally, compared to another 4 non-invasive liver fibrosis models (NFS = 0.66, FIB4 = 0.65, METS-IR = 0.68, APRI = 0.65), TyG-GGT exhibits the highest AUC value of 0.75. CONCLUSIONS: More than one-third of patients undergoing metabolic and bariatric surgery are afflicted with nonalcoholic steatohepatitis (NASH), and a significant proportion exhibit advanced fibrosis. TyG-GGT was a potentially reliable predictor for screening individuals with overweight or obesity at high risk of advanced liver fibrosis, thus providing clinical guidance for early intervention in this targeted group.

Visceral and ectopic fat are more predictively associated with primary liver cancer than overall obesity from genetic sights: A Mendelian randomization study.

Several observational studies have reported an association between obesity and primary liver cancer (PLC), while the causality behind this association and the comparison of the risk effects of different obesity indicators on PLC remain unclear. In this study, we performed two-sample Mendelian randomization (MR) analyses to assess the associations of genetically determined liver fat, visceral adipose tissue (VAT), and body mass index (BMI) with the risk of PLC. The summary statistics of exposures were obtained from two genome-wide association studies (GWASs) based on the UK Biobank (UKB) imaging cohort and the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. GWAS summary statistics for PLC were obtained from FinnGen consortium R7 release data, including 304 PLC cases and 218 488 controls. Inverse-variance weighted (IVW) was used as the primary analysis, and a series of sensitivity analyses were performed to further verify the robustness of these findings. IVW analysis highlighted a significant association of genetically determined liver fat (OR per SD increase: 7.14; 95% CI: 5.10-9.99; P = 2.35E-30) and VAT (OR per SD increase: 5.70; 95% CI: 1.32-24.72; P = .020) with PLC but not of BMI with PLC. The findings were further confirmed by a series of MR methods. No evidence of horizontal pleiotropy between these associations existed. Our study suggested that genetically determined liver fat and VAT rather than BMI were associated with an increased risk of PLC, which suggested that visceral fat distribution is more predictive of the clinical risk of PLC than common in vitro measures.