Prognostic Value of Invasion, Markers of Proliferation, and Classification of Giant Pituitary Tumors, in a Georeferred Cohort in Brazil of 50 Patients, with a Long-Term Postoperative Follow-Up
Pituitary adenomas are currently classified by histological, immunocytochemical and numerous ultrastructural characteristics lacking unequivocal prognostic correlations. We investigated the prognostic value of a new clinicopathological classification with grades based on invasion and proliferation. This retrospective multicentric case–control study comprised 410 patients who had surgery for a pituitary tumour with long-term follow-up. Using pituitary magnetic resonance imaging for diagnosis of cavernous or sphenoid sinus invasion, immunocytochemistry, markers of the cell cycle (Ki-67, mitoses) and p53, tumours were classified according to size (micro, macro and giant), type (PRL, GH, FSH/LH, ACTH and TSH) and grade (grade 1a: non-invasive, 1b: non-invasive and proliferative, 2a: invasive, 2b: invasive and proliferative, and 3: metastatic). The association between patient status at 8-year follow-up and age, sex, and classification was evaluated by two multivariate analyses assessing disease- or recurrence/progression-free status. At 8 years after surgery, 195 patients were disease-free (controls) and 215 patients were not (cases). In 125 of the cases the tumours had recurred or progressed. Analyses of disease-free and recurrence/progression-free status revealed the significant prognostic value (p < 0.001; p < 0.05) of age, tumour type, and grade across all tumour types and for each tumour type. Invasive and proliferative tumours (grade 2b) had a poor prognosis with an increased probability of tumour persistence or progression of 25- or 12-fold, respectively, as compared to non-invasive tumours (grade 1a). This new, easy to use clinicopathological classification of pituitary endocrine tumours has demonstrated its prognostic worth by strongly predicting the probability of post-operative complete remission or tumour progression and so could help clinicians choose the best post-operative therapy.