The Clinicopathologic Heterogeneity of Grade 3 Gastroenteropancreatic Neuroendocrine Neoplasms: Morphological Differentiation and Proliferation Identify Different Prognostic Categories

Massimo Milione, Patrick Maisonneuve, Francesca Spada, Alessio Pellegrinelli, Paola Spaggiari, Luca Albarello, Eleonora Pisa, Massimo Barberis, Alessandro Vanoli, Roberto Buzzoni, Sara Pusceddu, Laura Concas, F. Sessa, Enrico Solcia, Carlo Capella, Nicola Fazio, Stefano La Rosa

Research output: Contribution to journalArticle


Background/Aims: Gastroenteropancreatic (GEP) neuroendocrine carcinomas (NECs) are defined as neuroendocrine neoplasms (NENs) with >20% Ki-67 index according to the 2010 WHO classification. Some reports suggest that this category is heterogeneous. We retrospectively studied a series of 136 patients affected by grade 3 (G3) gastroenteropancreatic (GEP) neuroendocrine carcinomas (NECs) with the aim to clarify the prognostic role of tumor morphological differentiation, proliferation, defect in mismatch repair proteins (MMRd), CD117 expression, and site of origin. The primary endpoint was the correlation between these parameters and the overall survival (OS). Methods: Univariable and multivariable Cox proportional hazards regression analyses were used to assess the prognostic significance of various clinical and histopathologic features. Results: With a median follow-up of 81 months, the median OS was 12.9 months. At multivariate analysis, morphological differentiation, Ki67 index, MMRd, stage, and CD117 expression were independent prognostic markers in NECs. Three different prognostic categories of NECs were identified according to the degree of morphologic differentiation (well versus poorly-differentiated) and Ki67 index (

Original languageEnglish
Publication statusAccepted/In press - Mar 5 2016



  • Classification
  • Morphology
  • Neuroendocrine carcinoma
  • Prognosis
  • Proliferation

ASJC Scopus subject areas

  • Endocrinology
  • Endocrinology, Diabetes and Metabolism
  • Endocrine and Autonomic Systems
  • Cellular and Molecular Neuroscience

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