EPID-26. STEREOTACTIC RADIOSURGERY FOR CRANIAL NERVE METASTASES: A SINGLE INSTITUTION EXPERIENCE
Bibliographic record
Abstract
Abstract Cranial nerve metastases (CNM) can be primary via leptomeningeal metastasis or secondary by spread due to head and neck cancers or due to distant tumor metastasis to the skull base. In addition, they may cause cranial nerve-related symptoms that can impact patient quality of life. We performed a single-center retrospective cohort study of all patients with CNM treated with SRS at our institution between April 2003 and February 2021. Demographic and clinical information were retrieved from the electronic medical record. Median follow-up was 12.9 months. Our study cohort consisted of 9 patients with primary CNM and 8 with secondary CNM – for a total of 17 patients, with a total of 33 lesions (23 primary, 10 secondary). Eleven patients (64.7%) had symptoms caused by cranial nerve metastases. Symptoms were resolved in 5 of 11 patients (45.5%) after SRS. Patients with secondary CNM were more likely to have cranial nerve symptoms and more likely to have resolution of symptoms following SRS. The median time between SRS and symptom improvement was 3 months. Local tumor control was achieved in 30 of 33 lesions (90.9%). Local tumor control at 6 months and at 1 year were 100%. Our study suggests that SRS may be a safe and effective treatment for cranial nerve metastasis providing 90.9% local tumor control at final follow-up, and symptomatic stability or improvement in 90.9% of symptomatic cases. Patients with secondary CNM may stand to benefit more from a symptom management standpoint.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".