Does the Timing of Radiosurgery after Grade 1 Meningioma Resection Affect Long-Term Outcomes?
Bibliographic record
Abstract
BACKGROUND: Meningiomas are the most common benign intracranial tumors. Gamma Knife® stereotactic radiosurgery (GKSRS) has become a preferred management for recurrent or residual meningiomas. This study focuses on the relationship between tumor control and the time interval between resection of a World Health Organization (WHO) grade 1 meningioma and GKSRS. METHODS: This single institution retrospective analysis reviewed our experience in 238 patients who underwent GKSRS after a pathologically confirmed WHO grade 1 meningioma resection. The median follow-up was 7.4 years. The median aggregate tumor volume at GKSRS was 6 cm3 and a median margin dose of 13 Gy was utilized. Neurological symptoms were evident in 60% of patients at the time of procedure. RESULTS: Overall actuarial tumor control rates achieved were 91.3% at 5 years, 83.4% at 10 years, and 76% at 15 years. There were 35 patients (15%) who developed tumor progression within or directly adjacent to the GKSRS treatment field. The median time until progression was 6.3 years. The duration between surgical intervention and GKSRS did not show statistical significance at 3 months (p = 0.9), 6 months (p = 0.8), 12 months (p = 0.5), or 24 months (p = 0.9). Fifteen patients (6%) had tumor progression at an anatomically distinct location outside the GKSRS target volume. Neurological symptomatic improvement was more likely with early radiosurgery intervention (p = 0.007). CONCLUSION: Postoperative GKSRS was associated with excellent long-term tumor control for WHO grade 1 meningiomas, regardless of the interval after initial surgery. In addition, earlier radiosurgery was associated with superior symptom improvement.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".