Supplementary Material for: Prognostic Factors Across Poorly Differentiated Neuroendocrine Neoplasms: a Pooled Analysis

  • Giovanni Centonze (Contributore)
  • Patrick Maisonneuve (Contributore)
  • Natalie Prinzi (Contributore)
  • Sara Pusceddu (Contributore)
  • Luca Albarello (Contributore)
  • Eleonora Pisa (Contributore)
  • Massimo Barberis (Contributore)
  • Alessandro Vanoli (Contributore)
  • Paola Spaggiari (Contributore)
  • Paola Bossi (Contributore)
  • Laura Cattaneo (Contributore)
  • Giovanna Sabella (Contributore)
  • Enrico Solcia (Contributore)
  • Federica Grillo (Contributore)
  • Aldo Scarpa (Contributore)
  • Mauro Papotti (Contributore)
  • Marco Volante (Contributore)
  • Alessandro Mangogna (Contributore)
  • Stefano Ferrero (Contributore)
  • Luigi Rolli (Contributore)
  • Elisa Roca (Contributore)
  • Luisa Bercich (Contributore)
  • Mauro Benvenuti (Contributore)
  • Luca Messerini (Contributore)
  • Frediano Inzani (Contributore)
  • Giancarlo Pruneri (Contributore)
  • Adele Busico (Contributore)
  • Federica Perrone (Contributore)
  • Elena Tamborini (Contributore)
  • Alessio Pellegrinelli (Contributore)
  • Ketevani Kankava (Contributore)
  • Alfredo Berruti (Contributore)
  • Ugo Pastorino (Contributore)
  • Nicola Fazio (Contributore)
  • Fausto Sessa (Contributore)
  • Carlo Capella (Contributore)
  • Guido Rindi (Contributore)
  • Massimo Milione (Contributore)

Dataset

Description

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
Dati resi disponibili2022
EditoreKarger Publishers

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