Gérald Raverot1,2,3, Emmanuelle Dantony2,4,5, Julie Beauvy1,2, Alexandre Vasiljevic2,3,6, Sara Mikolasek1, Françoise Borson-Chazot1,2, Emmanuel Jouanneau2,3,7, Pascal Roy2,4,5, Jacqueline Trouillas2,6. 1. Fédération d'Endocrinologie, Groupement Hospitalier Est, Hospices Civils de Lyon, Bron F-69677, France. 2. Faculté de Médecine Lyon Est, Université Lyon 1, Lyon F-69372, France. 3. INSERM U1052, CNRS UMR5286, Cancer Research Centre of Lyon, Lyon F-69372, France. 4. Service de Biostatistique, Hospices Civils de Lyon, Lyon F-69003, France. 5. CNRS, UMR 5558, Equipe Biostatistique Santé, Villeurbanne F-69622, France. 6. Centre de Pathologie et de Biologie Est, Groupement Hospitalier Est, Hospices Civils de Lyon, Bron F-69677, France. 7. Service de Neurochirurgie, Groupement Hospitalier Est, Hospices Civils de Lyon, Bron F-69677, France.
Abstract
Background: Most pituitary neuroendocrine tumors (PitNETs) show benign behavior, but a substantial number are invasive, recur, or resist medical treatment. Based on a retrospective case-control study, we recently proposed a classification of PitNETs of prognostic relevance. This prospective study aims to test the value of this classification in an independent patient cohort. Methods: All patients who underwent PitNET surgery from 2007 to 2012 in one single center were included. Using a grading system based on invasion on magnetic resonance imaging, immunocytochemical profile, Ki-67, mitotic index, and p53 positivity, tumors were classified. Progression-free survival of the graded tumors was calculated by the Kaplan-Meier method and compared using the log-rank test. A multivariate analysis, using a Cox regression model, was also performed. Results: In total, 365 patients had grade 1a PitNETs (51.2%), followed by grade 2a (32.3%), 2b (8.8%), and 1b tumors (7.7%). Of 213 patients with a follow-up, 42% had recurrent (n = 52) or progressive disease (n = 37) at 3.5 years. Grade was a significant predictor of progression-free survival (P < 0.001). Multivariate analysis indicated grade (P < 0.001), age (P = 0.035), and tumor type (P = 0.028) as independent predictors of recurrence and/progression. This risk was 3.72-fold higher for a grade 2b tumor compared with grade 1a tumor. Conclusions: Our data suggest that classification of PitNETs into five grades is of prognostic value to predict postoperative tumor behavior and identifies patients who have a high risk of early recurrence or progression. It therefore will allow clinicians to adapt their therapeutic strategies and stratify patients in future clinical trials.
Background: Most pituitary neuroendocrine tumors (PitNETs) show benign behavior, but a substantial number are invasive, recur, or resist medical treatment. Based on a retrospective case-control study, we recently proposed a classification of PitNETs of prognostic relevance. This prospective study aims to test the value of this classification in an independent patient cohort. Methods: All patients who underwent PitNET surgery from 2007 to 2012 in one single center were included. Using a grading system based on invasion on magnetic resonance imaging, immunocytochemical profile, Ki-67, mitotic index, and p53 positivity, tumors were classified. Progression-free survival of the graded tumors was calculated by the Kaplan-Meier method and compared using the log-rank test. A multivariate analysis, using a Cox regression model, was also performed. Results: In total, 365 patients had grade 1a PitNETs (51.2%), followed by grade 2a (32.3%), 2b (8.8%), and 1b tumors (7.7%). Of 213 patients with a follow-up, 42% had recurrent (n = 52) or progressive disease (n = 37) at 3.5 years. Grade was a significant predictor of progression-free survival (P < 0.001). Multivariate analysis indicated grade (P < 0.001), age (P = 0.035), and tumor type (P = 0.028) as independent predictors of recurrence and/progression. This risk was 3.72-fold higher for a grade 2b tumor compared with grade 1a tumor. Conclusions: Our data suggest that classification of PitNETs into five grades is of prognostic value to predict postoperative tumor behavior and identifies patients who have a high risk of early recurrence or progression. It therefore will allow clinicians to adapt their therapeutic strategies and stratify patients in future clinical trials.
Authors: P D Delgado-López; J Pi-Barrio; M T Dueñas-Polo; M Pascual-Llorente; M C Gordón-Bolaños Journal: Clin Transl Oncol Date: 2018-04-05 Impact factor: 3.405
Authors: C Villa; A Vasiljevic; M L Jaffrain-Rea; O Ansorge; S Asioli; V Barresi; L Chinezu; M P Gardiman; A Lania; A M Lapshina; L Poliani; L Reiniger; A Righi; W Saeger; J Soukup; M Theodoropoulou; S Uccella; J Trouillas; F Roncaroli Journal: Virchows Arch Date: 2019-10-02 Impact factor: 4.064
Authors: Sam Ng; Mahmoud Messerer; Julien Engelhardt; Michaël Bruneau; Jan Frederick Cornelius; Luigi Maria Cavallo; Giulia Cossu; Sebastien Froelich; Torstein R Meling; Dimitrios Paraskevopoulos; Henry W S Schroeder; Marcos Tatagiba; Idoya Zazpe; Moncef Berhouma; Roy T Daniel; Edward R Laws; Engelbert Knosp; Michael Buchfelder; Henri Dufour; Stéphane Gaillard; Timothée Jacquesson; Emmanuel Jouanneau Journal: Acta Neurochir (Wien) Date: 2021-08-08 Impact factor: 2.816