Prostate Cancer Metastasis to the Pituitary Gland Manifesting as Corticosteroid Withdrawal, and the Impact of the Switch from Prednisone to Dexamethasone on Survival Time
Bibliographic record
Abstract
Despite improvements in the diagnosis and treatment of cancers, the incidence of pituitary metastasis has increased. Prostate cancer metastasis to the pituitary, however, is rare, and these tumors usually grow rapidly. They are also more likely to be located in the posterior pituitary, and the presenting symptoms are often nonspecific, which makes early diagnosis challenging. The management of this condition is usually multidisciplinary, and requires careful assessment and decision making. We present a case of a patient who developed prostate cancer metastasis to the pituitary. In this report, we show that patients with prostate cancer on corticosteroid therapy who develop withdrawal symptoms or other endocrine symptoms should be assessed for pituitary and other brain metastasis. This case report also discusses the impact of switching from prednisone and abiraterone to dexamethasone and abiraterone. Our report shows that patients on abiraterone and prednisone whose PSA has increased, but who have no radiologic progression, may have their PSA controlled and thereby improved survival time when they are switched to abiraterone and dexamethasone.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".