Pancreaticobiliary endoscopy, encompassing endoscopic ultrasound (EUS), endoscopic retrograde cholangiopancreatography (ERCP), and digital single-operator cholangioscopy (DSOC), is essential for diagnosing and managing pancreatic and biliary diseases. However, these procedures are limited by operator dependency, variable diagnostic accuracy, and technical complexity. Artificial intelligence (AI), particularly through machine learning (ML) and deep learning (DL), has emerged as a promising tool to address these challenges. Early studies show that AI can enhance lesion detection, improve differentiation of pancreatic masses, classify cystic lesions, and aid in diagnosing malignant biliary strictures. AI has also been used to predict post-ERCP pancreatitis risk and reduce radiation exposure during ERCP. Despite this promise, current AI models are largely experimental—limited by small, single-center datasets, lack of external validation, and no FDA-approved systems for these indications. Major barriers include inconsistent data acquisition, limited interoperability across hardware platforms, and integration into real-time workflows. Future progress depends on multicenter data sharing, standardized imaging protocols, interpretable AI design, and regulatory pathways for model deployment and updates. AI can be developed as a valuable partner to endoscopists, enhancing diagnostic accuracy, reducing complications, and supporting more efficient, personalized care in pancreaticobiliary endoscopy.

Background: Peritoneal metastasis represents an aggressive disease pattern in pancreatic ductal adenocarcinoma (PDAC), traditionally associated with poor survival and limited therapeutic options. Emerging intraperitoneal chemotherapy strategies—including hyperthermic intraperitoneal chemotherapy (HIPEC), normothermic intraperitoneal paclitaxel (NIPEC/IP-PTX), and pressurized intraperitoneal aerosol chemotherapy (PIPAC)—have been investigated to improve local tumor control and survival outcomes. Methods: We systematically reviewed published studies evaluating HIPEC, NIPEC/IP-PTX, and PIPAC in PDAC, including adjuvant, cytoreductive, and palliative settings. Study characteristics, feasibility, perioperative outcomes, oncologic outcomes, and risk of bias were analyzed. Results: Across modalities, intraperitoneal treatment strategies demonstrated acceptable feasibility and safety profiles in appropriately selected patients. Adjuvant HIPEC following pancreatectomy showed reduced local–regional recurrence signals in limited cohorts. CRS + HIPEC among patients with isolated peritoneal metastases yielded encouraging multi-year survival in highly selected candidates achieving complete cytoreduction. NIPEC/IP-PTX demonstrated favorable ascites control, symptom relief, and potential conversion to resection in select patients. PIPAC was primarily used in unresectable, heavily pretreated, palliative peritoneal metastasis settings, with goals centered on disease stabilization, histologic regression, and symptom control rather than curative intent. Conclusions: Intraperitoneal chemotherapy strategies in PDAC appear feasible with signals of meaningful clinical benefit in select settings. While CRS + HIPEC may benefit carefully selected metastatic patients, NIPEC/IP-PTX and PIPAC hold value primarily in symptom control and disease stabilization. Larger prospective trials are needed to define patient selection, optimize treatment protocols, and clarify survival benefit.

Immune checkpoint inhibitors (ICIs) have transformed the treatment landscape for relapsed or refractory classical Hodgkin lymphoma (cHL); however, a substantial subset of patients ultimately requires allogeneic hematopoietic stem cell transplantation (allo-HCT) to achieve long-lasting disease control. The use of ICIs as a bridge to allo-HCT has therefore gained increasing clinical interest, though concerns persist regarding post-transplant complications and incompletely-defined safety profiles. Accordingly, this systematic review and meta-analysis was conducted to evaluate outcomes of ICIs administered prior to allo-HCT in cHL. Following PRISMA guidelines, a comprehensive literature search was conducted across online databases through January 2026. Eligible studies included observational designs reporting survival and transplant-related outcomes in cHL patients treated with ICIs followed by allo-HCT. Pooled proportions for overall survival, progression-free survival, non-relapse mortality, and graft-versus-host disease (GVHD) incidence were calculated using a random-effects model. Seven studies comprising 739 patients were included. Post-transplant survival outcomes were favorable, with high pooled estimates across timepoints. Transplant-related mortality remained low, with NRM rates consistently within an acceptable range through long-term follow-up. Acute GVHD was observed at a meaningful frequency, including a smaller subset of severe cases, while chronic GVHD occurred in approximately one-quarter of patients at follow-up. Overall, these findings suggest that ICI therapy prior to allo-HCT in cHL is associated with encouraging survival and disease control and does not appear to confer excessive non-relapse mortality, supporting its use as a feasible and effective bridging strategy, while underscoring the need for future prospective studies to clarify optimal timing, risk mitigation strategies, and patient selection.

PURPOSE: Immune checkpoint inhibitors (ICIs) have transformed cancer care but impose a growing financial burden on Medicare. We characterized Medicare Part B spending and utilization patterns for ICIs from 2018 to 2022 to quantify expenditure trends and identify key cost drivers. METHODS: We conducted a retrospective analysis of the Centers for Medicare & Medicaid Services (CMS) Medicare Part B Spending by Drug public summary files (aggregated Healthcare Common Procedure Coding System [HCPCS] drug-year data) from 2018 through 2022. For eight ICIs, we extracted total gross program spending, total dosage units (HCPCS billing units), and unique beneficiaries and calculated average spending per dosage unit, average spending per beneficiary, and growth metrics over time. RESULTS: In 2022, total Medicare Part B spending across the eight ICIs was approximately $8.49 billion US dollars (USD). Pembrolizumab accounted for the largest spending ($4.94 billion USD) and beneficiary utilization (67,022 beneficiaries), followed by nivolumab ($1.85 billion USD; 26,957 beneficiaries). Average spending per beneficiary in 2022 (the primary cost metric, capturing dose frequency and treatment duration) ranged from $53,508 USD (durvalumab) to $80,705 USD (atezolizumab). Average spending per dosage unit varied widely as a secondary pricing measure, from $27.02 USD (cemiplimab) to $216.09 USD (dostarlimab). CONCLUSION: Medicare Part B spending on ICIs is highly concentrated among pembrolizumab and nivolumab, and is driven primarily by beneficiary volume, with substantial heterogeneity in per-beneficiary spending across agents. As indications and utilization continue to expand, these therapies' fiscal impact warrants ongoing evaluation to inform Medicare payment policy and value-based oncology care.