Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia · 2026
The role of preoperative medical therapy on prolactin normalization following prolactinoma resection: evaluating longitudinal prolactin trajectories using linear mixed-effects modeling.
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Papisetty Karthik, McCaffery Thomas, Duggireddy Hithardhi, Salmeron-Moreno Karen, Kashlan Rommi, Buclez Josephine, Theodore John, Donghyun Kim Chris, Minseo Kim Jennifer, Valiveti Karthik, Thakar Uday, Hu Derek, Janarthanan Nyneishia, Maldonado Justin, Pradilla Gustavo, Garzon-Muvdi Tomas
Аннотация
BACKGROUND: Optimal treatment sequencing between medical therapy with dopamine agonists and surgical intervention remains debated in prolactinoma management. Understanding whether preoperative medical therapy influences postoperative prolactin normalization trajectories is critical for guiding treatment decisions and patient counseling. We evaluated longitudinal prolactin dynamics after surgery and tested whether preoperative medical therapy influences hormonal recovery rate.
METHODS: We retrospectively analyzed 142 patients with prolactinomas who underwent surgical resection between 2000 and 2024 at a single institution. Patients were divided into two cohorts: those who received preoperative dopamine agonist therapy (DAT) prior to surgery (combined medical and surgical, n = 103) and those who underwent first-line surgery (surgical-only, n = 39). Prolactin levels were assessed preoperatively and at fixed timepoints postoperatively. Linear mixed-effects models, Cox proportional hazards regression, and cross-sectional comparisons were used to evaluate postoperative prolactin trajectories and predictors of biochemical remission.
RESULTS: Treatment modality did not independently predict postoperative prolactin levels, biochemical remission rates, or rate of prolactin change over time in either the primary 1-year or extended 5-year models. A significant selection effect was identified, whereby postoperative DAT initiation was driven by prolactin elevation rather than treatment group assignment. Baseline prolactin level was the dominant predictor of both time to biochemical remission and time to DAT initiation on Cox regression.
CONCLUSION: Preoperative DAT exposure does not independently influence long-term postoperative prolactin trajectories following surgical resection. Baseline prolactin burden, rather than treatment sequencing, is the primary determinant of postoperative prolactin control and should be central to prognostic discussions with patients.
METHODS: We retrospectively analyzed 142 patients with prolactinomas who underwent surgical resection between 2000 and 2024 at a single institution. Patients were divided into two cohorts: those who received preoperative dopamine agonist therapy (DAT) prior to surgery (combined medical and surgical, n = 103) and those who underwent first-line surgery (surgical-only, n = 39). Prolactin levels were assessed preoperatively and at fixed timepoints postoperatively. Linear mixed-effects models, Cox proportional hazards regression, and cross-sectional comparisons were used to evaluate postoperative prolactin trajectories and predictors of biochemical remission.
RESULTS: Treatment modality did not independently predict postoperative prolactin levels, biochemical remission rates, or rate of prolactin change over time in either the primary 1-year or extended 5-year models. A significant selection effect was identified, whereby postoperative DAT initiation was driven by prolactin elevation rather than treatment group assignment. Baseline prolactin level was the dominant predictor of both time to biochemical remission and time to DAT initiation on Cox regression.
CONCLUSION: Preoperative DAT exposure does not independently influence long-term postoperative prolactin trajectories following surgical resection. Baseline prolactin burden, rather than treatment sequencing, is the primary determinant of postoperative prolactin control and should be central to prognostic discussions with patients.