Risk of new tumor, carotid stenosis, and stroke after stereotactic radiosurgery for pituitary tumor: A multicenter study of 2254 patients with imaging follow-up
Bibliographic record
Abstract
BACKGROUND: A higher risk of secondary brain tumor, carotid stenosis, and stroke has been reported after conventional sella irradiation for pituitary neuroendocrine tumors (PitNET). Stereotactic radiosurgery (SRS), which is a more focused approach, is now increasingly used instead. The aim was to assess the risk of secondary brain tumor, carotid stenosis/occlusion, and stroke after SRS. METHODS: In this multicentric retrospective study, 2254 patients with PitNET were studied, 1377 in the exposed group, and 877 in the control group. RESULTS: There were 9840.1 patient-years at risk for the SRS and 5266.5 for the control group. The 15-year cumulative probability of secondary intracranial tumor was 2.3% (95% CI: 0.5%, 4.1%) for SRS and 3.7% (95% CI: 0%, 8.7%) for the control group (P = .6), with an incidence rate of 1.32 per 1000 and 0.95 per 1000, respectively. SRS was not associated with an increased risk of tumorigenesis when stratified by age (HR: 1.59 [95% CI: 0.57, 4.47], Pp = .38). The 15-year probability of new carotid stenosis/occlusion was 0.9% (95% CI: 0.2, 1.6) in the SRS and 2% (95% CI: 0, 4.4) in the control group (P = .8). The 15-year probability of stroke was 2.6% (95% CI: 0.6%, 4.6%) in the SRS and 11.1% (95% CI: 6%, 15.9%) in the control group (P < .001). In Cox multivariate analysis stratified by age, SRS (HR 1.85 [95% CI:0.64, 5.35], P = .26) was not associated with risk of new stroke. CONCLUSIONS: No increased risk of long-term secondary brain tumor, new stenosis or occlusion, and stroke was demonstrated in the SRS group compared to the control in this study with imaging surveillance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".