Introduction: Poorly differentiated neuroendocrine carcinomas (NECs) are characterized by aggressive clinical course and poor prognosis. No reliable prognostic markers have been validated to date; thus, the definition of a specific NEC prognostic algorithm represents a clinical need. This study aimed to analyze a large NEC case series to validate the specific prognostic factors identified in previous studies on gastro-entero-pancreatic (GEP) and lung NECs and to assess if further prognostic parameters can be isolated. Methods: A pooled analysis of four NEC retrospective studies was performed to evaluate: the prognostic role of Ki-67 cut-off, the OS according to primary cancer site, and further prognostic parameters using multivariable Cox proportional hazards model and machine-learning random survival forest (RSF). Results: 422 NECs were analyzed. The most represented tumor site was the colorectum (n=156, 37%), followed by the lungs (n=111, 26%), gastroesophageal site (n=83, 20%; 66 gastric, 79%). The Ki-67 index was the most relevant predictor, followed by morphology (pure or mixed/combined NECs), stage, and site. The predicted RSF response for survival at 1, 2, or 3 years showed decreasing survival with increasing Ki-67, pure NEC morphology, stage III–IV, and colorectal NEC disease. Patients with Ki-67 <55% and mixed/combined morphology had better survival than those with pure morphology. Morphology pure or mixed/combined became irrelevant in NECs survival when Ki-67 was ≥55%. The prognosis of metastatic patients who did not receive any treatment tended to be worse compared to that of the treated group. The prognostic impact of Rb1 immunolabeling appears to be limited when multiple risk factors are simultaneously assessed. Conclusion: The most effective parameters to predict OS for NEC patients could be Ki-67, pure or mixed/combined morphology, stage, and site.

Introduction: Poorly differentiated neuroendocrine carcinomas (NECs) are characterized by aggressive clinical course and poor prognosis. No reliable prognostic markers have been validated to date; thus, the definition of a specific NEC prognostic algorithm represents a clinical need. This study aimed to analyze a large NEC case series to validate the specific prognostic factors identified in previous studies on gastro-entero-pancreatic (GEP) and lung NECs and to assess if further prognostic parameters can be isolated. Methods: A pooled analysis of four NEC retrospective studies was performed to evaluate: the prognostic role of Ki-67 cut-off, the OS according to primary cancer site, and further prognostic parameters using multivariable Cox proportional hazards model and machine-learning random survival forest (RSF). Results: 422 NECs were analyzed. The most represented tumor site was the colorectum (n=156, 37%), followed by the lungs (n=111, 26%), gastroesophageal site (n=83, 20%; 66 gastric, 79%). The Ki-67 index was the most relevant predictor, followed by morphology (pure or mixed/combined NECs), stage, and site. The predicted RSF response for survival at 1, 2, or 3 years showed decreasing survival with increasing Ki-67, pure NEC morphology, stage III–IV, and colorectal NEC disease. Patients with Ki-67 <55% and mixed/combined morphology had better survival than those with pure morphology. Morphology pure or mixed/combined became irrelevant in NECs survival when Ki-67 was ≥55%. The prognosis of metastatic patients who did not receive any treatment tended to be worse compared to that of the treated group. The prognostic impact of Rb1 immunolabeling appears to be limited when multiple risk factors are simultaneously assessed. Conclusion: The most effective parameters to predict OS for NEC patients could be Ki-67, pure or mixed/combined morphology, stage, and site.