Background: Gastro-entero-pancreatic neuroendocrine tumors (GEP-NETs) are the most prevalent subgroup among NETs and include heterogeneous tumors characterized by different clinical behavior and prognosis. The NETest is a tool based on real-time PCR combined with deep learning strategies to specifically identify tumors with a neuroendocrine genotype. Despite the promising results achieved regarding its utility in the field of GEP-NETs, the NETest has not yet entered into routine clinical practice. Methods: We performed a systematic review aimed at summarizing available evidence on the application of the NETest in both the diagnosis and the prognostic stratification of GEP-NETs. Results: We identified five studies evaluating the diagnostic role of the NETest and nine studies evaluating its prognostic value. The NETest emerged as a reliable biomarker for GEP-NET diagnosis with an accuracy higher than 90%, regardless of tumor stage and grade. However, according to some studies, the NETest showed a low specificity, mainly attributed to interferences with other gastro-intestinal malignancies. In terms of prognostic value, the NETest correlated with the detection of residual disease after surgery in six studies. The NETest was also associated with patients' survival outcomes, namely progression-free survival (PFS) and overall survival (OS) in three studies. Conclusions: According to current systematic review, the value of the NETest both for diagnosis and for prognosis of GEP-NET emerged as robust across different studies. Further prospective analysis on larger GEP-NET series is encouraged to validate this tool, improving patients' diagnosis, management, and follow-up.

NETest and Gastro-Entero-Pancreatic Neuroendocrine Tumors: Still Far from Routine Clinical Application? A Systematic Review

Rossi, Roberta Elisa;
2025-01-01

Abstract

Background: Gastro-entero-pancreatic neuroendocrine tumors (GEP-NETs) are the most prevalent subgroup among NETs and include heterogeneous tumors characterized by different clinical behavior and prognosis. The NETest is a tool based on real-time PCR combined with deep learning strategies to specifically identify tumors with a neuroendocrine genotype. Despite the promising results achieved regarding its utility in the field of GEP-NETs, the NETest has not yet entered into routine clinical practice. Methods: We performed a systematic review aimed at summarizing available evidence on the application of the NETest in both the diagnosis and the prognostic stratification of GEP-NETs. Results: We identified five studies evaluating the diagnostic role of the NETest and nine studies evaluating its prognostic value. The NETest emerged as a reliable biomarker for GEP-NET diagnosis with an accuracy higher than 90%, regardless of tumor stage and grade. However, according to some studies, the NETest showed a low specificity, mainly attributed to interferences with other gastro-intestinal malignancies. In terms of prognostic value, the NETest correlated with the detection of residual disease after surgery in six studies. The NETest was also associated with patients' survival outcomes, namely progression-free survival (PFS) and overall survival (OS) in three studies. Conclusions: According to current systematic review, the value of the NETest both for diagnosis and for prognosis of GEP-NET emerged as robust across different studies. Further prospective analysis on larger GEP-NET series is encouraged to validate this tool, improving patients' diagnosis, management, and follow-up.
2025
NETest
diagnosis
gastro-entero-pancreatic neuroendocrine tumors
personalized medicine
prognosis
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11699/106187
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