Effect of Anatomic Segment Involvement on Stereotactic Radiosurgery for Facial Nerve Schwannomas: An International Multicenter Cohort Study
Bibliographic record
Abstract
BACKGROUND: Facial nerve schwannomas are rare, challenging tumors to manage due to their nerve of origin. Functional outcomes after stereotactic radiosurgery (SRS) are incompletely defined. OBJECTIVE: To analyze the effect of facial nerve segment involvement on functional outcome for these tumors. METHODS: Patients who underwent single-session SRS for facial nerve schwannomas with at least 3 mo follow-up at 11 participating centers were included. Preoperative and treatment variables were recorded. Outcome measures included radiological tumor response and neurological function. RESULTS: A total of 63 patients (34 females) were included in the present study. In total, 75% had preoperative facial weakness. Mean tumor volume and margin dose were 2.0 ± 2.4 cm3 and 12.2 ± 0.54 Gy, respectively. Mean radiological follow-up was 45.5 ± 38.9 mo. Progression-free survival at 2, 5, and 10 yr was 98.1%, 87.2%, and 87.2%, respectively. The cumulative proportion of patients with regressing tumors at 2, 5, and 10 yr was 43.1%, 63.6%, and 63.6%, respectively. The number of involved facial nerve segments significantly predicted tumor progression (P = .04). Facial nerve function was stable or improved in 57 patients (90%). Patients with involvement of the labyrinthine segment of the facial nerve were significantly more likely to have an improvement in facial nerve function after SRS (P = .03). Hearing worsened in at least 6% of patients. Otherwise, adverse radiation effects included facial twitching (3 patients), facial numbness (2 patients), and dizziness (2 patients). CONCLUSION: SRS for facial nerve schwannomas is effective and spares facial nerve function in most patients. Some patients may have functional improvement after treatment, particularly if the labyrinthine segment is involved.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".