Comparison of Active Surveillance to Stereotactic Radiosurgery for the Management of Patients with an Incidental Frontobasal Meningioma—A Sub-Analysis of the IMPASSE Study
Bibliographic record
Abstract
Meningioma is a common incidental finding, and clinical course varies based on anatomical location. The aim of this sub-analysis of the IMPASSE study was to compare the outcomes of patients with an incidental frontobasal meningioma who underwent active surveillance to those who underwent upfront stereotactic radiosurgery (SRS). Data were retrospectively collected from 14 centres. The active surveillance (n = 28) and SRS (n = 84) cohorts were compared unmatched and matched for age, sex, and duration of follow-up (n = 25 each). The study endpoints included tumor progression, new symptom development, and need for further intervention. Tumor progression occurred in 52.0% and 0% of the matched active surveillance and SRS cohorts, respectively (p < 0.001). Five patients (6.0%) treated with SRS developed treatment related symptoms compared to none in the active monitoring cohort (p = 0.329). No patients in the matched cohorts developed symptoms attributable to treatment. Three patients managed with active surveillance (10.7%, unmatched; 12.0%, matched) underwent an intervention for tumor growth with no persistent side effects after treatment. No patients subject to SRS underwent further treatment. Active monitoring and SRS confer a similarly low risk of symptom development. Upfront treatment with SRS improves imaging-defined tumor control. Active surveillance and SRS are acceptable treatment options for incidental frontobasal meningioma.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".