Neuroendocrine Neoplasm Clinical Trial
Official title:
Definition of a Multiparametric Prognostic and Predictive System of Classification of NET G3 Patients: an observAtional, Prospective Analysis of the Correlation Between Functional Imaging and Clinical Outcome (TAPIOCA)
The 2017 World Health Organization (WHO) introduced a new category of high-grade, well-differentiated neuroendocrine neoplasms (NENs) that called neuroendocrine tumors (NETs) G3 in pancreatic NENs classification and, then, in 2019, for all gastro-entero-pancreatic (GEP) tract NENs. The new classification made it possible to separate NETs G3 from high-grade, poorly-differentiated, NENs that are called neuroendocrine carcinomas (NECs). However, in clinical practice, we observed that several clinical, pathological and radiological differences are arising among NET G3 patients, suggesting that a multiparametric definition of NET G3 is needed.
High-grade neuroendocrine neoplasms (NENs) represent the poorest prognosis category within NENs. During the years, the prognostic differences among the subgroups led to identify at least two subcategories of high-grade NENs, according the morphologic features of the two subtypes. Indeed, the 2017 World Health Organization (WHO) introduced a new category of high-grade, well-differentiated NENs that called neuroendocrine tumors (NETs) G3 for pancreatic NENs and, then, in 2019, for all gastro-entero-pancreatic (GEP) tract NENs, allowing to separate NET G3 from the other high-grade, poorly-differentiated, NENs, so called neuroendocrine carcinomas (NECs). However, since the new-category has been introduced, NET G3 category seemed to be more heterogeneous than presumed. Indeed, clinical, pathological and radiological features seemed to identify different prognostic subcategories of NET G3. We recently performed a retrospective analysis on a small pool of 48 NET G3 patients, correlating the clinical outcomes with these different features. The results of our study seemed to suggest prognostic and predictive factors that deserve to be prospectively explored to better understand this pathology and that might to be part of NET G3 multiparametric classification system. Based on the results of our retrospective analysis, we underlined the importance of a systematic and well-designed collection of high-quality data in order to improve our knowledge on this topic. ;
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