Documented Initial Growth Does Not Necessarily Indicate Treatment for Sporadic Vestibular Schwannomas
Bibliographic record
Abstract
OBJECTIVE: To report the natural history of vestibular schwannoma (VS) who elected an initial period of observation and identify prognostic factors. To describe the natural history of growing VS, identify prognostic factors, and review the most recent literature. STUDY DESIGN: Prospective cohort study and literature review. SETTING: Tertiary referral center. PATIENTS: Adult patients diagnosed with a VS between January 1998 and February 2023. INTERVENTION: Magnetic resonance imaging surveillance. MAIN OUTCOME MEASURES: Growth-free survival and subsequent growth-free survival considering significant growth as a change in size of ≥2 mm. RESULTS: Of 430 patients undergoing observation with serial magnetic resonance imaging, 193 (44.9%) demonstrated significant growth at a median of 1.6 years (interquartile range, 0.94-3.51). Of the 193 patients who presented an initial episode of growth, 137 elected to continue to be observed. Of those, 83 (60.6%) presented a second episode of growth at a median of 1.43 years (interquartile range, 1.00-2.49). The subsequent growth-free survival rates (95% confidence interval) at 1, 3, 5, 7, and 10 years were 91.79% (87.26-96.56%), 64.44% (56.56-73.42%), 52.52% (44.23-62.35%), 42.23% (33.92-52.56%), and 36.11% (27.89-46.76%), respectively. Univariate and multivariate Cox regression analyses showed that EC tumor location and initial growth rate were significant predictors of subsequent growth. CONCLUSIONS: Close observation after documentation of growth is an appropriate management in well-selected cases given that only around 56% of the tumor will continue to grow. Extracanalicular tumor location and initial growth rate are promising prognostic factors to help determine which patient would be a better candidate for close surveillance after initial documentation of growth.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".