A Machine Learning Algorithm Facilitates Prognosis Prediction and Treatment Selection for Barcelona Clinic Liver Cancer Stage C Hepatocellular Carcinoma.

PURPOSE: Given its heterogeneity and diverse clinical outcomes, precise subclassification of Barcelona Clinic Liver Cancer stage C (BCLC-C) hepatocellular carcinoma (HCC) is required for appropriately determining patient prognosis and selecting treatment. EXPERIMENTAL DESIGN: We recruited 2,626 patients with BCLC-C HCC from multiple centers, comprising training/test (n = 1,693) and validation cohorts (n = 933). The XGBoost model was chosen for maximum performance among the machine learning (ML) models. Patients were categorized into low-, intermediate-, high-, and very high-risk subgroups based on the estimated prognosis, and this subclassification was named the CLAssification via Machine learning of BCLC-C (CLAM-C). RESULTS: The areas under the receiver operating characteristic curve of the CLAM-C for predicting the 6-, 12-, and 24-month survival of patients with BCLC-C were 0.800, 0.831, and 0.715, respectively-significantly higher than those of the conventional models, which were consistent in the validation cohort. The four subgroups had significantly different median overall survivals, and this difference was maintained among various patient subgroups and treatment modalities. Immune-checkpoint inhibitors and transarterial therapies were associated with significantly better survival than tyrosine kinase inhibitors (TKI) in the low- and intermediate-risk subgroups. In cases with first-line systemic therapy, the CLAM-C identified atezolizumab-bevacizumab as the best therapy, particularly in the high-risk group. In cases with later-line systemic therapy, nivolumab had better survival than TKIs in the low-to-intermediate-risk subgroup, whereas TKIs had better survival in the high- to very high-risk subgroup. CONCLUSIONS: ML modeling effectively subclassified patients with BCLC-C HCC, potentially aiding treatment allocation. Our study underscores the potential utilization of ML modeling in terms of prognostication and treatment allocation in patients with BCLC-C HCC.

Sequential double-guidewire technique and transpancreatic precut sphincterotomy for difficult biliary cannulation.

BACKGROUND/AIMS: The double-guidewire technique (DGT) and transpancreatic precut sphincterotomy (TPS) are introduced as alternative biliary cannulation techniques for difficult biliary cannulation. This study aimed to evaluate the sequential use of DGT and TPS compared with a needle-knife precut papillotomy (NK). PATIENTS AND METHODS: Six hundred and thirty-five consecutive patients with naοve papilla and who underwent endoscopic retrograde cholangiopancreatography (ERCP) for biliary cannulation from March 2010 to April 2014 in a single institute were analyzed. When standard techniques were unsuccessful, DGT or NK was performed. TPS was sequentially performed if DGT failed. RESULTS: DGT and NK were attempted in 65 and 58 patients, respectively. A sequential DGT-TPS was performed in 38 patients after a failed DGT. Biliary cannulations were successful in 42%, 74%, and 66% of the DGT, sequential DGT-TPS, and NK patients, respectively (P = 0.002). The cannulation rate was higher in the DGT ± TPS patients (85%) than in the NK patients (P = 0.014). Post-ERCP pancreatitis (PEP) developed in 26% of the successful DGT patients, 37% of the sequential DGT-TPS patients, and 10% of the NK patients (P = 0.008). Of the sequential DGT-TPS patients, the incidence of PEP was significantly reduced in patients with a pancreatic duct (PD) stent compared with patients without a PD stent (24% vs. 62%, P = 0.023). CONCLUSIONS: Sequential DGT-TPS is a useful alternative method compared with NK for patients in whom biliary cannulation is difficult. In the sequential DGT-TPS patients, the incidence of PEP was significantly reduced with the use of a PD stent.

Doxorubicin-polyphosphazene conjugate hydrogels for locally controlled delivery of cancer therapeutics.

Poly(organophosphazene)-doxorubicin (DOX) conjugate bearing hydrophobic L-isoleucine ethyl ester (IleOEt) and hydrophilic alpha-amino-omega-methoxy-poly(ethylene glycol) with molecular weight of 550 Da (AMPEG 550) along with carboxylic acid as a functional group was synthesized to create a drug delivery system, which is based on locally injectable, biodegradable, and thermosensitive hydrogels. In addition to the evaluation of the in vitro and in vivo antitumor activities, the physicochemical properties, hydrolytic degradation, and DOX release profile of the poly(organophosphazene)-DOX conjugate were determined. The aqueous solution of the polymer-DOX conjugate showed a sol-gel transition behavior depending on temperature changes. Based on the in vivo antitumor activities of the locally injected poly(organophosphazene)-DOX conjugate into the tumor-induced nude mice, the conjugate hydrogel after the local injection at the tumor site was shown to inhibit tumor growth more effectively with less toxicity and much longer than doxorubicin and saline as controls, indicating that tumor active DOX from the conjugate hydrogel is released slowly over a longer period of time and effectively accumulated locally in the tumor sites. These results suggest that the poly(organophosphazene)-doxorubicin conjugates hold great potential for use in preclinical and clinical studies as single and/or combination therapies.

Effects of activated carbon types and service life on removal of endocrine disrupting chemicals: amitrol, nonylphenol, and bisphenol-A.

Removal performances of endocrine disrupting chemicals (EDC) such as amitrol, nonylphenol, and bisphenol-A were evaluated in this study using granular activated carbon (GAC) adsorption. This study found that GAC adsorption was effective in removal of EDCs with high K(ow) value. Nonylphenol and bisphenol-A were effectively adsorbed onto all carbons (including the used carbons) tested in this study. As indicated by K(ow) value, nonylphenol was more effectively adsorbed than bisphenol-A. The coal-based carbon was found more effective than other carbons in the adsorption of nonylphenol and bisphenol-A due to its larger pore volume. The adsorption capacity reduced with the operation year, and the extent of the reduction was different depending upon the carbon type and the operation year. Amitrol was effectively removed by biological degradation, but was poorly adsorbed. Since the microbes residing at the used carbons already accustomed to amitrol, the used carbons removed amitrol better than the virgin carbons. Although the coal-based carbon showed the best removal performance of amitrol, GAC adsorption could not be recommended for amitrol removal because considerable portion of incoming amitrol (9-87%) passed through GAC adsorption column. According to this study, pore volume mainly influenced the adsorption capacity, but the surface charge was also important due to electrical interaction. The adsorption parameters for nonylphenol and bisphenol-A provided by this study could be valuable when GAC adsorption was considered to handle an accidental spill of nonylphenol and bisphenol-A.