ACTH‐secreting Crooke cell carcinoma of the pituitary
Bibliographic record
Abstract
PURPOSE: While pituitary adenomas are common, pituitary carcinomas are rare. It is unclear whether pituitary carcinomas arise de novo or evolve from adenomas. METHODS: We studied the clinical characteristics and tissue samples from eight pituitary surgeries and the autopsy from a patient with pituitary carcinoma. A 16-year-old female patient was diagnosed with an aggressive Crooke cell macroadenoma. Following transsphenoidal surgery, clinical signs of Cushing disease quickly reappeared. During the 14-year course of the illness, eight pituitary surgeries, three courses of extracranial irradiation and two (90) Yttrium-DOTATOC treatments were undertaken. A bilateral adrenalectomy was performed. The patient died of metastatic disease and uncontrolled hypercortisolism due to an adrenal remnant. A systematic morphologic study (histologic staining, electron microscopy) of all available surgical and autopsy specimens was undertaken. RESULTS: Brisk mitotic activity, high Ki-67 and p53 immunolabelling were present in the pituitary samples from the onset. High proportion of tumour cells showed irregular nuclei and large nucleoli, and gradual increase in MGMT staining was observed. The tumour remained of Crooke cell type throughout the course. Autopsy disclosed a postirradiation sarcoma in the pituitary area. CONCLUSIONS: The question whether pituitary carcinomas arise de novo or transform from an adenoma cannot be answered at present with certainty.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".