Fong, Zhi Ven

ABSTRACT Background and Objectives There is increasing use of neoadjuvant treatment (NAT) for patients with pancreatic adenocarcinoma (PDAC). The role of additional adjuvant chemotherapy (AT) is not well‐defined. This study aims to determine the impact of lymphovascular invasion (LVI) and lymph node (LN) involvement on overall survival (OS) in patients with resected PDAC and determine the impact of AT after NAT. Methods This is an observational cohort study of patients with PDAC who underwent NAT and surgical resection. A multivariable model was used to assess for differences in OS. An interaction term between LVI or LN involvement and AT use was utilized to test the benefit of additional AT. Results Seven thousand four hundred and fourteen patients were included; group A (LVI‐, LN‐) had 2787 patients, B (LVI + , LN‐) 652, C (LVI‐, LN + ) 1,712, and D (LVI + , LN + ) 2263. Median OS differed significantly between groups, A had the most favorable survival (34.1 months), followed by B (27.8 months), C (26.3 months), and D (21.2 months, p < 0.001). In patients with persistent LVI or LN involvement after NAT, additional AT was not associated with OS (group A, HR: 0.94, p = 0.4; B and C, HR: 1.0, p = 0.99; D, HR: 0.94, p = 0.32). Conclusions LVI and LN involvement were independently associated with worse OS. After NAT, the use of AT in patients with persistent LVI and LN involvement was not associated with improved OS.

The authors explore the association of remnant cholesterol and CRP with the longitudinal development of cancer in a prospective cohort study and if there is an opportunity to modulate risk with bariatric surgery or GLP‐1 agonist.

AbstractWith the proliferation of cancer research based on large databases, misalignment of research questions and data set capabilities is inevitable. Nationally maintained databases are appealing to cancer researchers because of the ease of access to large amounts of patient data available for analysis and risk estimation. Data sets that are commonly used in cancer research include the National Cancer Database, the SEER (Surveillance, Epidemiology, and End Results) program of the National Cancer Institute, the SEER–Medicare database, the American College of Surgeons National Surgical Quality Improvement Program, and the Healthcare Cost and Utilization Project databases, among others. Each data set has pros and cons with respect to variable availability and the ability to analyze cancer‐specific outcomes. It is critical for researchers to understand the strengths and limitations of each database. Changing variable definitions, the length of postoperative data collection, and the availability of patient‐reported outcomes or social determinants of health data are examples of factors that researchers must consider when selecting a data set for research purposes. For the current review, the authors summarized the advantages and disadvantages of various national data sets for cohort studies in cancer populations.

The incidence of pancreatic neuroendocrine tumors (PNETs) is on the rise primarily due to the increasing use of cross-sectional imaging. Most of these incidentally detected lesions are non-functional PNETs with a small proportion of lesions being hormone-secreting, functional neoplasms. With recent advances in surgical approaches and systemic therapies, the management of PNETs have undergone a paradigm shift towards a more individualized approach. In this manuscript, we review the histologic classification and diagnostic approaches to both functional and non-functional PNETs. Additionally, we detail multidisciplinary approaches and surgical considerations tailored to the tumor’s biology, location, and functionality based on recent evidence. We also discuss the complexities of metastatic disease, exploring liver-directed therapies and the evolving landscape of minimally invasive surgical techniques.

The incidence of biliary tract cancer in Ontario, Canada, is rising, highlighting the urgency of clinical trial enrollment to move the needle in cancer‐specific outcomes. The integration of natural language processing and population registries demonstrate the immense potential of future generation registries in allowing us to more accurately discern population‐level data.