Infiltration pattern predicts metastasis and progression better than the T-stage and grade in pancreatic neuroendocrine tumors: a proposal for a novel infiltration-based morphologic grading

The advancing edge profile is a powerful determinant of tumor behavior in many organs. In this study, a grading system assessing the tumor-host interface was developed and tested in 181 pancreatic neuroendocrine tumors (PanNETs), 63 of which were <=2 cm. Three tumor slides representative of the spectrum (least, medium, and most) of invasiveness at the advancing edge of the tumor were selected, and then each slide was scored as follows. Well-demarcated/encapsulated, 1 point; Mildly irregular borders and/or minimal infiltration into adjacent tissue, 2 points; Infiltrative edges with several clusters beyond the main tumor but still relatively close, and/or satellite demarcated nodules, 3 points; No demarcation, several cellular clusters away from the tumor, 4 points; Exuberantly infiltrative pattern, scirrhous growth, dissecting the normal parenchymal elements, 5 points. The sum of the rankings on the three slides was obtained. Cases with scores of 3-6 were defined as "non/minimally infiltrative" (NI; n = 77), 7-9 as "moderately infiltrative" (MI; n = 68), and 10-15 as "highly infiltrative" (HI; n = 36). In addition to showing a statistically significant correlation with all the established signs of aggressiveness (grade, size, T-stage), this grading system was found to be the most significant predictor of adverse outcomes (metastasis, progression, and death) on multivariate analysis, more strongly than T-stage, while Ki-67 index did not stand the multivariate test. As importantly, cases <=2 cm were also stratified by this grading system rendering it applicable also to this group that is currently placed in "watchful waiting" protocols. In conclusion, the proposed grading system has a strong, independent prognostic value and therefore should be considered for integration into routine pathology practice after being evaluated in validation studies with larger series.