Comparison of the long-term outcomes of patients with hepatocellular carcinoma within the Milan criteria treated by ablation, resection, or transplantation.

BACKGROUND: Liver transplantation (LT), resection (LR), and ablation (LA) are three curative-intent treatment options for patients with early hepatocellular carcinoma (HCC). We aimed to develop a prognostic calculator to compare the long-term outcomes following each of these therapies. METHODS: A total of 976 patients with HCC within the Milan criteria who underwent LT, LR, and LA between 2009 and 2019 from four institutions were evaluated. Multistate competing risks prediction models for recurrence-free survival (RFS), recurrence within the Milan criteria (RWM), and HCC-specific survival (HSS) were derived to develop a prognostic calculator. RESULTS: During a median follow-up of 51 months, 420 (43%) patients developed recurrence. In the multivariate analysis, larger tumor size, multinodularity, older age, male, higher alpha-fetoprotein (AFP), higher albumin-bilirubin (ALBI) grade, and the presence of portal hypertension were significantly associated with higher recurrence and decreased survival rates. The RFS and HSS were both significantly higher among patients treated by LT than by LR or LA and significantly higher between patients treated by LR than by LA (all p < 0.001). For multinodular HCC ≤3 cm, although LT had better RFS and HSS than LR or LA, LA was noninferior to LR. An online prognostic calculator was then developed based on the preoperative clinical factors that were independently associated with outcomes to evaluate RFS, RWM, and HSS at different time intervals for all three treatment options. CONCLUSIONS: Although LT resulted in the best recurrence and survival outcomes, LR and LA also offered durable long-term alternatives. This prognostic calculator is a useful tool for clinicians to guide an informed and personalized discussion with patients based on their tumor biology and liver function.

A Novel Nomogram Model to Predict the Recurrence-Free Survival and Overall Survival of Hepatocellular Carcinoma.

Background: Treatments for patients with early-stage hepatocellular carcinoma (HCC) include liver transplantation (LT), liver resection (LR), radiofrequency ablation (RFA), and microwave ablation (MWA), are critical for their long-term survival. However, a computational model predicting treatment-independent prognosis of patients with HCC, such as overall survival (OS) and recurrence-free survival (RFS), is yet to be developed, to our best knowledge. The goal of this study is to identify prognostic factors associated with OS and RFS in patients with HCC and develop nomograms to predict them, respectively. Methods: We retrospectively retrieved 730 patients with HCC from three hospitals in China and followed them up for 3 and 5 years after invasive treatment. All enrolled patients were randomly divided into the training cohort and the validation cohort with a 7:3 ratio, respectively. Independent prognostic factors associated with OS and RFS were determined by the multivariate Cox regression analysis. Two nomogram prognostic models were built and evaluated by concordance index (C-index), calibration curves, area under the receiver operating characteristics (ROC) curve, time-dependent area under the ROC curve (AUC), the Kaplan-Meier survival curve, and decision curve analyses (DCAs), respectively. Results: Prognostic factors for OS and RFS were identified, and nomograms were successfully built. Calibration discrimination was good for both the OS and RFS nomogram prediction models (C-index: 0.750 and 0.746, respectively). For both nomograms, the AUC demonstrated outstanding predictive performance; the DCA shows that the model has good decision ability; and the calibration curve demonstrated strong predictive power. The nomograms successfully discriminated high-risk and low-risk patients with HCC associated with OS and RFS. Conclusions: We developed nomogram survival prediction models to predict the prognosis of HCC after invasive treatment with acceptable accuracies in both training and independent testing cohorts. The models may have clinical values in guiding the selection of clinical treatment strategies.

Comparison of Liver Transplantation and Liver Resection for Hepatocellular Carcinoma Patients with Portal Vein Tumor Thrombus Type I and Type II.

PURPOSE: The aim of this study was to compare the efficacy of liver transplantation (LT) and liver resection (LR) for hepatocellular carcinoma (HCC) patients with portal vein tumor thrombus (PVTT) and to investigate risk factors affecting prognosis. MATERIALS AND METHODS: A total of 94 HCC patients with PVTT type I (segmental PVTT) and PVTT type II (lobar PVTT) were involved and divided into LR (n=47) and LT groups (n=47). Recurrence-free survival (RFS) and overall survival (OS) were compared before and after inverse probability of treatment weighting (IPTW). Prognostic factors for RFS and OS were explored. RESULTS: Two treatment groups were well-balanced using IPTW. In the entire cohort, LT provided a better prognosis than LR. Among patients with PVTT type I, RFS was better with LT (p=0.039); OS was not different significantly between LT and LR (p=0.093). In subgroup analysis of PVTT type I patients with α-fetoprotein (AFP) levels >200 ng/mL, LT elicited significantly longer median RFS (18.0 months vs. 2.1 months, p=0.022) and relatively longer median OS time (23.6 months vs. 9.8 months, p=0.065). Among patients with PVTT type II, no significant differences in RFS and OS were found between LT and LR (p=0.115 and 0.335, respectively). Multivariate analyses showed treatment allocation (LR), tumor size (>5 cm), AFP and aspartate aminotransferase (AST) levels to be risk factors of RFS and treatment allocation (LR), AFP and AST as risk factors for OS. CONCLUSION: LT appeared to afford a better prognosis for HCC with PVTT type I than LR, especially in patients with AFP levels >200 ng/mL.

Two decoupling methods for non-isothermal DSC results of AIBN decomposition.

During thermal decomposition of azobisisobutyronitrile (AIBN), the endothermic process of phase transition disturbed exothermic decomposition, which brought deformation in its thermal graphs. Therefore, exact kinetic parameters of the decomposition could not be obtained by the existing kinetics analytic models, and the accurate enthalpy data of the decomposition and phase transition were not available. Two methods, i.e., a solvent method and a mathematical method, were introduced in this paper to resolve the coupling phenomenon. In the former method, AIBN was dissolved into aniline to eliminate the endothermic process and obtain curves of the liquid-state decomposition. In the latter method, MATLAB software was employed to get the "pure" exothermic decomposition curve without the influence of phase transition by fitting coupling curves within the section after the transition point and extrapolating to the initial stage of decomposition. Moreover, the kinetic parameters of the "pure" exothermic decomposition of AIBN obtained by the mathematical fitting agreed with the results from the solvent method, verifying the accuracy of the decoupling. The research is of great significance for comprehending the exact characteristics of thermal behaviors and safety parameters of AIBN. It also provides a great help to determine the safe operating temperature and alarm temperature for processes in industry.