Stereotactic Radiosurgery for Atypical (World Health Organization II) and Anaplastic (World Health Organization III) Meningiomas: Results From a Multicenter, International Cohort Study
Bibliographic record
Abstract
BACKGROUND: Atypical and anaplastic meningiomas have reduced progression-free/overall survival (PFS/OS) compared to benign meningiomas. Stereotactic radiosurgery (SRS) for atypical meningiomas (AMs) and anaplastic meningiomas (malignant meningiomas, MMs) has not been adequately described. OBJECTIVE: To define clinical/radiographic outcomes for patients undergoing SRS for AM/MMs. METHODS: An international, multicenter, retrospective cohort study was performed to define clinical/imaging outcomes for patients receiving SRS for AM/MMs. Tumor progression was assessed with response assessment in neuro-oncology (RANO) criteria. Factors associated with PFS/OS were assessed using Kaplan-Meier analysis and a Cox proportional hazards model. RESULTS: A total of 271 patients received SRS for AMs (n = 233, 85.9%) or MMs (n = 38, 14.0%). Single-fraction SRS was most commonly employed (n = 264, 97.4%) with a mean target dose of 14.8 Gy. SRS was used as adjuvant treatment (n = 85, 31.4%), salvage therapy (n = 182, 67.2%), or primary therapy (1.5%). The 5-yr PFS/OS rate was 33.6% and 77.0%, respectively. Increasing age (hazard ratio (HR) = 1.01, P < .05) and a Ki-67 index > 15% (HR = 1.66, P < .03) negatively correlated with PFS. MMs (HR = 3.21, P < .05), increased age (HR = 1.04, P = .04), and reduced KPS (HR = 0.95, P = .04) were associated with shortened OS. Adjuvant versus salvage SRS did not impact PFS/OS. A shortened interval between surgery and SRS improved PFS for AMs (HR = 0.99, P = .02) on subgroup analysis. Radiation necrosis occurred in 34 (12.5%) patients. Five-year rates of repeat surgery/radiation were 33.8% and 60.4%, respectively. CONCLUSION: AM/MMs remain challenging tumors to treat. Elevated proliferative indices are associated with tumor recurrence, while MMs have worse survival. SRS can control AM/MMs in the short term, but the 5-yr PFS rates are low, underscoring the need for improved treatment options for these patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| 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".