Defining Biological Borderline Resectable Non-Functioning Pancreatic Neuroendocrine Tumors (NF-PanNETs): A Predictive Model for Preoperative Assessment of Early Recurrence Risk.

Abstract

OBJECTIVE This study aimed to develop and validate a preoperative predictive model to identify patients at high risk of early recurrence (ER), with a view to establish a framework for biological borderline resectability of non-functioning pancreatic neuroendocrine tumors (NF-PanNETs). SUMMARY BACKGROUND DATA Radical surgery is curative for most localized NF-PanNETs, but a subset of patients experiences ER. No standardized criteria define preoperative high-risk disease. METHODS A retrospective multicentric study was conducted at three tertiary centers. Patients undergoing curative resection for localized NF-PanNETs were included, and preoperative clinicopathological and imaging variables were analyzed. ER was defined as a recurrence within 24 months. A classification tree model was developed, and performance was assessed using the AUC of the ROC curve. RESULTS A total of 496 patients were analyzed, with 290 in the derivation cohort and 206 in the validation cohort. ER occurred in 55 patients (11%), including 26 (9%) in the derivation and 29 (14%) in the validation cohort. The median disease-free survival for ER patients was 16 months (IQR: 10-20 months). Neoplastic venous thrombosis was the strongest predictor of ER, with an ER probability of 71%. Among patients without venous thrombosis, those with a Ki-67 index ≥5% and tumor size ≥3 cm had an ER probability of 41% in case of adenopathy and 19% otherwise. The model achieved an AUC of 0.91 in the derivation cohort and 0.84 in the validation cohort. CONCLUSIONS This externally validated model provides a reliable preoperative tool to identify NF-PanNETs at high-risk of ER and introduces the concept of biological borderline resectable NF-PanNETs.