What would you do? A survey of HPB surgeons practice patterns.

BACKGROUND: The surgical decision making for pancreatic adenocarcinoma is complex. Although practice guidelines exist for many scenarios, these do not cover many common eventualities that may be encountered during these cases. We sought to identify the practice pattern variations amongst pancreatic surgeons in response to commonly experienced clinical scenarios. METHODS: A multiple-choice questionnaire was distributed to all full members of the IHPBA. Participant demographics, training history, and clinical practice information were obtained. The survey provided various operative scenarios and participants were asked how they would likely proceed. Responses were collected and stored anonymously in a secure database. Statistical analysis was performed using Stata 16.0. RESULTS: 164 responses were submitted. Most of the respondents were male and had been in practice for over 10 years. The median age range was 40-50 years old. When asked about staging laparoscopy, the majority performed it selectively. For most respondents a pathological aorto-caval nodes was a reason to abort the procedure but most would have continued in the setting of a positive hepatic artery node. When encountering a single Segment 2 liver metastasis, participants who practiced in Europe were significantly more likely to resect and proceed compared to those in Asia and North America. Participants who had undergone only a Surgical Oncology fellowship were most likely to abort. With respect to direct colonic invasion, most participants would resect the specimen en bloc. Respondents who participated in fewer that 20 PDAC operations/year were most likely to abort. CONCLUSIONS: Surgical decision making in PDAC surgery is complex and there is significant disagreement on the correct management. While formal guidelines cannot exist for all situations, this survey highlights the need for consensus on commonly encountered operative scenarios.

It's more than just cancer biology: Health disparities in patients with pancreatic neuroendocrine tumors.

BACKGROUND AND OBJECTIVES: Pancreatic neuroendocrine tumors (PNETs) represent a rare form of pancreatic cancer. Racial/ethnic disparities have been documented in pancreatic ductal adenocarcinoma, but health disparities have not been well described in patients with PNETs. METHODS: A retrospective review of patients with PNETs in the National Cancer Database was performed for 2004-2014. Approximately 16 605 patients with PNETs and available vital status were identified. Survival was compared by race/ethnicity and socioeconomic status using Kaplan-Meier methods and Cox regression. RESULTS: There were no significant differences in survival between Non-Hispanic, White; Hispanic, White; or Non-Hispanic, Black patients on univariate analysis. Kaplan-Meier analysis showed that patients from communities with lower median household income and education level had worse survival (p < 0.001). Patients age less than 65 without insurance, similarly, had worse survival (p < 0.001). Multivariable modeling found no association between race/ethnicity and risk of mortality (p = 0.37). Lower median household income and lower education level were associated with increased mortality (p < 0.001). CONCLUSIONS: Unlike most other malignancies, race/ethnicity is not associated with survival differences in patients with PNETs. Patients with lower socioeconomic status had worse survival. The presence of identifiable health disparities in patients with PNETs represents a target for intervention and opportunity to improve survival in patients with this malignancy.

Prognostic Impact of Tumor Size on Pancreatic Neuroendocrine Tumor Recurrence May Have Racial Variance.

OBJECTIVE: The incidence of pancreatic neuroendocrine tumors (PNETs) has increased over the last decade. Black patients have worse survival outcomes. This study investigates whether oncologic outcomes are racially disparate at a single institution. METHODS: Retrospective analysis was performed on 151 patients with resected PNETs between 2010 and 2019. RESULTS: More White males and Black females presented with PNETs (P = 0.02). White patients were older (65 years vs 60 years; P = 0.03), more likely to be married (P < 0.01), and had higher median estimated yearly incomes ($28,973 vs $17,767; P < 0.01) than Black patients. Overall and disease-free survival were not different. Black patients had larger median tumor sizes (30 mm vs 23 mm; P = 0.02). Tumor size was predictive of recurrence only for White patients (hazard ratio, 1.02; P = 0.01). Collectively, tumors greater than 20 mm in size were more likely to have recurrence (P = 0.048), but this cutoff was not predictive in either racial cohort independently. CONCLUSIONS: Black patients undergoing curative resection of PNETs at our institution presented with larger tumors, but that increased size is not predictive of disease-free survival in this population.

Ex Vivo Modeling of Human Neuroendocrine Tumors in Tissue Surrogates.

Few models exist for studying neuroendocrine tumors (NETs), and there are mounting concerns that the currently available array of cell lines is not representative of NET biology. The lack of stable patient-derived NET xenograft models further limits the scientific community's ability to make conclusions about NETs and their response to therapy in patients. To address these limitations, we propose the use of an ex vivo 3D flow-perfusion bioreactor system for culturing and studying patient-derived NET surrogates. Herein, we demonstrate the utility of the bioreactor system for culturing NET surrogates and provide methods for evaluating the efficacy of therapeutic agents on human NET cell line xenograft constructs and patient-derived NET surrogates. We also demonstrate that patient-derived NET tissues can be propagated using the bioreactor system and investigate the near-infrared (NIR) dye IR-783 for its use in monitoring their status within the bioreactor. The results indicate that the bioreactor system and similar 3D culture models may be valuable tools for culturing patient-derived NETs and monitoring their response to therapy ex vivo.