BACKGROUND:In the hepatitis B e antigen positive (HBeAg+) chronic infection disease phase, approved treatments have limited effects on hepatitis B surface antigen (HBsAg) and HBeAg. OBJECTIVE:The phase 2 REEF-IT study (NCT04439539) assessed safety, efficacy and pharmacokinetics of pegylated interferon-α2a (PegIFN-α2a) add-on to JNJ-73763989 (JNJ-3989)±bersacapavir+nucleos(t)ide analogues (NA) in not currently treated, HBeAg+chronic hepatitis B. DESIGN:Participants received JNJ-3989 (200 mg every 4 weeks)+NA±bersacapavir (250 mg daily) for 36-52 weeks (induction) followed by 12 weeks of PegIFN-α2a (180 µg weekly) add-on. The primary endpoint was the proportion of participants with HBsAg seroclearance 24 weeks after stopping all treatment including NA. Changes in viral markers, safety and pharmacokinetics were assessed. RESULTS:49/54 (91%) enrolled participants completed the study; 52% were male, with mean age of 33.6 years. No participant achieved the primary endpoint; one met NA completion criteria. 11/54 (20.4%) participants achieved HBsAg seroclearance at least once, 6 of them maintained it until Follow-up Week 48 (FUW48). Overall mean (SE) change from baseline in HBsAg of -2.85 (0.13), -3.61 (0.18) and -2.63 (0.26)log10IU/mL were observed at end of induction, end of treatment and FUW48. 16/53 (30.2%) participants reached HBeAg seroclearance at least once; 12 maintained it until FUW48. Similar proportions of participants experienced an adverse event (AE) during induction (83.3%), PegIFN-α2a add-on (85.7%) and follow-up (64.7%). There were no deaths or serious AEs; two participants discontinued PegIFN-α2a. CONCLUSIONS:In this population, adding PegIFN-α2a increased HBsAg declines after reductions by JNJ-3989; 20.4% achieved HBsAg seroclearance at least once. Treatment was generally safe with acceptable tolerability. TRIAL REGISTRATION NUMBER:NCT04439539.
Although prompt treatment is desirable for malignancies, surgical delays are sometimes unavoidable. Previous studies show conflicting results on the effect of diagnosis-to-surgery delay in esophageal cancer, mainly focusing on advanced stages treated preoperatively. Early stage disease, particularly cT1bN0, often involves longer waiting times, but the acceptable delay remains unclear. We conducted this study to evaluate the impact of surgical waiting time on postoperative survival in patients with clinical T1bN0M0 esophageal squamous cell carcinoma (ESCC) undergoing upfront esophagectomy. This multicenter retrospective study included 160 patients with cT1bN0M0 ESCC undergoing subtotal esophagectomy with lymphadenectomy at seven Japanese institutions between 2008 and 2021. Receiver operating characteristic (ROC) analysis identified the optimal waiting time cutoff predicting recurrence. Survival outcomes were compared between short and long waiting groups using the Kaplan–Meier method and Cox regression analyses. ROC analysis identified 66.5 days as the optimal cutoff value. The long waiting group (≥ 67 days) showed significantly worse 3-year recurrence-free survival (87.9
Non-alcoholic fatty liver disease (NAFLD) is one of the most prevalent causes of chronic liver disease, and strategies to prevent NAFLD-related hepatocellular carcinoma and liver failure are of increasing importance. Recently, the classification of steatotic liver disease (SLD) has been redefined based on alcohol intake: metabolic dysfunction-associated SLD (MASLD, mild alcohol intake), MASLD and increased alcohol intake (MetALD, moderate alcohol intake), and alcohol-related liver disease (ALD, heavy alcohol intake). Because the concordance rate between NAFLD and MASLD is 96–99
Background Liver resection (LR) and radiofrequency ablation (RFA) are recommended for patients with up to three hepatocellular carcinomas (HCCs) measuring ≤3 cm and preserved liver function. Nevertheless, treatment allocation is decided according to the preference of the treating doctor. This study aimed to develop a predictive model to guide treatment decisions based on survival outcomes. Methods A total of 18,958 patients with HCC with up to three nodules measuring ≤3 cm were included from the nationwide survey of Japan. Deep survival analysis was performed using the Recurrent Deep Survival Machines (RDSM) model. Model performance was evaluated using 10-fold cross-validation, concordance index (C-index), and overall survival (OS). Survival curves were compared using the log-rank test. Potential confounding factors were identified using 1:1 propensity score matching (PSM). Results Patients who underwent LR showed significantly longer OS than those who underwent RFA (5-year survival rate 81.4% vs. 73.1%; P < 0.005). The trained RDSM model achieved a C-index of 0.68. In the deep learning (DL) model, patients who received the recommended treatment exhibited significantly longer survival than those who did not (5-year survival rate 81.2% vs. 73.9%; P < 0.005; PSM, 81.9% vs. 76.7%; P < 0.005). The DL model recommended LR in 6,966 (84.5%) patients who received RFA, especially those exhibiting typical imaging patterns (early enhancement and washout in the computed tomography (CT) images [85.9% vs. 61.7% and 84.1 vs.74.3%, respectively]). Conclusions DL modeling effectively helped treatment allocation for patients with HCC with up to three nodules measuring ≤3 cm. Our study indicates the potential utilization of DL modeling in the treatment allocation of these patients.
