The Vanishing Pituitary Tumor: A Case Report
Bibliographic record
Abstract
Prolactinomas are the most common functional pituitary tumors and present with elevated serum prolactin levels. This may or may not be accompanied by mass-related clinical symptoms. Dopamine agonists are its principal treatment. Data on prolactinoma remission and relapse after treatment withdrawal are limited. Here we report a patient presenting with headache, amenorrhea, galactorrhea, visual field impairments and a high serum prolactin level. After a definitive diagnosis of pituitary macroadenoma, the patient was treated with bromocriptine. Twelve months after treatment, tumor size markedly reduced, there was resolution of symptoms and patient was eventually lost to follow-up. After 10 months without treatment, tumor recurred. Bromocriptine was resumed for 5 more years and discontinued thereafter. Since then, the patient has been asymptomatic for the past 12 years; surveillance imaging showed no tumor recurrence with annual prolactin level all within normal range. This case adds to the limited data confirming that dopamine agonists in patients with prolactinomas can be successfully discontinued with a high remission rate, provided that there is adequate duration of treatment and sufficient follow-up. J Endocrinol Metab. 2021;11(3-4):91-93 doi: https://doi.org/10.14740/jem753
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".