4.7 Article

Risk of Recurrence in Pituitary Neuroendocrine Tumors: A Prospective Study Using a Five-Tiered Classification

Journal

JOURNAL OF CLINICAL ENDOCRINOLOGY & METABOLISM
Volume 102, Issue 9, Pages 3368-3374

Publisher

ENDOCRINE SOC
DOI: 10.1210/jc.2017-00773

Keywords

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Funding

  1. Ministere de la Sante Programme Hospitalier de Recherche Clinique National Grant Hypophyse Pronostique (HYPOPRONOS) [2743]
  2. Programme Hospitalier de Recherche Clinique National Institut National du Cancer (INCA) Pituitary Tumor Identification of Genetic markers (PITUIGENE) [12-096]

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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.

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