Gamma Knife radiosurgery for the treatment of Nelson’s syndrome: a multicenter, international study
Bibliographic record
Abstract
OBJECTIVE: Nelson's syndrome is a rare and challenging neuroendocrine disorder, and it is associated with elevated adrenocorticotrophic hormone (ACTH) level, skin hyperpigmentation, and pituitary adenoma growth. Management options including resection and medical therapy are traditional approaches. Ionizing radiation in the form of Gamma Knife radiosurgery (GKRS) is also being utilized to treat Nelson's syndrome. In the current study the authors sought to better define the therapeutic role of stereotactic radiosurgery (SRS) in Nelson's syndrome. METHODS: Study patients with Nelson's syndrome were treated with single-fraction GKRS (median margin dose of 25 Gy) at 6 different centers as part of an International Radiosurgery Research Foundation (IRRF) investigation. Data including neurological function, endocrine response, and radiological tumor response were collected and sent to the study-coordinating center for review. Fifty-one patients with median endocrine and radiological follow-ups of 91 and 80.5 months from GKRS, respectively, were analyzed for endocrine remission, tumor control, and neurological outcome. Statistical methods were used to identify prognostic factors for these endpoints. RESULTS: At last follow-up, radiological tumor control was achieved in 92.15% of patients. Endocrine remission off medical management and reduction in pre-SRS ACTH level were achieved in 29.4% and 62.7% of patients, respectively. Improved remission rates were associated with a shorter time interval between resection and GKRS (p = 0.039). Hypopituitarism was seen in 21.6% and new visual deficits were demonstrated in 15.7% of patients. CONCLUSIONS: GKRS affords a high rate of pituitary adenoma control and improvement in ACTH level for the majority of Nelson's syndrome patients. Hypopituitarism is the most common adverse effect from GKRS in Nelson's syndrome patients and warrants longitudinal follow-up for detection and endocrine replacement.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".