Risk-Stratifying Pituitary Adenoma Treatment: A Cohort Analysis and Risk Prediction of Hypopituitarism

Background/Objectives: The management of pituitary adenomas involves balancing treatment efficacy with the risk of long-term morbidity, particularly treatment-induced hypopituitarism. While risk factors are qualitatively recognized, quantitative, individualized risk prediction tools for clinical practice are lacking. This study aims to evaluate and characterize the clinical features, hormonal profiles, and treatment outcomes of pituitary adenomas, and to develop and validate a pragmatic clinical prediction model for new-onset hypopituitarism. Methods: We conducted a retrospective cohort study of 215 patients diagnosed with pituitary adenomas, selected from 647 sellar lesions screened at a tertiary referral center between January 2010 and December 2020. Primary outcomes included adenoma size control, hormonal remission in functioning adenomas, and the development of new-onset hypopituitarism. A multivariable logistic regression model was developed to identify independent predictors of new-onset hypopituitarism, and its performance was assessed for discrimination and calibration. Results: The cohort consisted of 107 prolactinomas (49.8%), 77 non-functioning adenomas (35.8%), 18 GH-secreting (8.4%), and 8 ACTH-secreting (3.7%) adenomas, with a mean age of 43.2 ± 14.1 years and a female predominance (59.1%). At a median follow-up of 4.8 years, overall adenoma control was 92.1%. Radiotherapy achieved 100% adenoma control but was associated with the highest incidence of new hypopituitarism at 5 years (34.3%), significantly greater than medical therapy (5.6%, p < 0.001) and surgery (13.0%, p < 0.01). The final risk prediction model, incorporating treatment modality, baseline hypopituitarism, macroadenoma, age >50 years, and cavernous sinus invasion, demonstrated good discrimination (C-statistic = 0.82; 95% CI: 0.76-0.88) and excellent calibration (Hosmer-Lemeshow p = 0.42). Conclusions: Treatment modalities for pituitary adenomas have distinct risk-benefit profiles. Our validated, points-based risk model provides a transparent and clinically applicable tool to quantify an individual patient's risk of developing hypopituitarism. This model can be integrated into clinical practice to facilitate shared decision-making and guide personalized surveillance strategies.