Distinguishing Prolactinoma from Nonfunctioning Pituitary Adenoma with Hyperprolactinemia by Clinical, Laboratory, and Imaging Characteristics

Introduction: Distinguishing between prolactinoma and nonfunctioning pituitary adenoma (NFPA) exhibiting stalk effect can be difficult, as such tumors do not often segregate cleanly by prolactin level or imaging characteristics. Establishing this distinction is crucial because the first-line management to date is dopaminergic agonists in prolactinomas and surgery in NFPAs of sufficient size.

Methods: Patients surgically treated for prolactinoma or NFPA from 1993-2022 were retrospectively reviewed. We collected patient, clinical, and radiographic characteristics such as tumor dimensions and volume, pituitary gland and optic chiasm visibility, cavernous sinus invasion, and degrees of stalk tilt. Each patient’s highest-recorded preoperative prolactin level was matched with the closest available MRI scan. Multivariate logistic models identified predictors associated with a prolactinoma diagnosis. The selected model’s discriminative capacity was evaluated through a receiver operating characteristics (ROC) curve and measured by area under the curve (AUC). A nomogram was then generated as a visualizing aid.

Results: We included 274 patients with 291 pituitary adenoma resections: 73 (25%) prolactinomas and 218 (75%) NFPAs. Tumor was recurrent in 49 (17%) and previously resected in 57 (20%) cases. Cavernous sinus invasion was present in 75 (26%) cases. The derived multivariate logistic model contained the following prolactinoma predictors: microadenoma (odds ratio [OR]=12.81 (2.48-66.23); p=0.002), younger age (OR=0.96 (0.93-0.99); p=0.006), galactorrhea (OR=3.92 (1.04-14.69); p=0.043), and greater highest preoperative prolactin level (OR=2.62 (1.89-3.63); p< 0.0001). The AUC was 0.937 (95% CI: 0.898, 0.976). Tumor volume did not correlate with the highest preoperative prolactin level in prolactinomas (r= 0.089; p=0.56) or NFPAs (r= -0.07; p=0.33).

Conclusion : Tumor volume alone may be insufficient to predict tumor type with accuracy. Rather, a combination of clinical and imaging features best distinguishes prolactinomas from NFPAs exhibiting stalk effect. The nomogram derived from this study provides a predictive tool that helps direct clinical management in patients presenting with a sellar tumor and hyperprolactinemia.