RADT-38. DOSE ESCALATED RADIOTHERAPY IS ASSOCIATED WITH IMPROVED OUTCOMES FOR HIGH GRADE MENINGIOMA
Bibliographic record
Abstract
Abstract BACKGROUND The optimal modern radiotherapy (RT) approach after surgery for atypical and malignant meningioma is unclear. We present results of dose-escalation. METHODS Consecutive patients with histopathologic grade 2 or 3 meningioma treated with RT were reviewed. A dose-escalation cohort [≥ 66Gy equivalent dose in 2 Gy fractions using an a/b = 10 (EQD2)], was compared to a standard dose cohort (< 66Gy). Outcomes were progression-free survival (PFS), cause-specific survival (CSS), overall survival (OS), local failure (LF) and radiation necrosis. RESULTS 118 patients (111 Grade 2, 94.1%) were identified; 54/118 (45.8%) received dose-escalation and 64/118 (54.2%) standard dose. Median follow-up was 45.4 months (IQR: 24.0 - 80.0 months) and median OS was 9.7 years (Q1: 4.6 years, Q3: not reached). All dose-escalated patients had residual disease vs. 65.6% in the standard dose cohort (p < 0.001). PFS at 3-, 4- and 5-years in the dose-escalated vs. standard dose cohort were 78.9%, 72.2% and 64.6% vs. 57.2%, 49.1% and 40.8%, respectively, (p = 0.030). On multivariable (MVA) analysis, dose-escalation (HR: 0.544,p = 0.042) was associated with improved PFS, whereas ≥ 2 surgeries (HR: 1.989, p = 0.035) and older age (HR: 1.035, p < 0.001) were associated with worse PFS. The cumulative risk of LF was reduced with dose-escalation (p = 0.016). MVA confirmed dose-escalation protective for LF (HR: 0.483, p = 0.019), whereas ≥ 2 surgeries prior to RT predicted for LF (HR: 2.145, p = 0.008). A trend was observed for improved CSS and OS in the dose-escalation cohort (p < 0.1). Seven patients (5.9%) developed symptomatic radiation necrosis (RN) with no significant difference between the two cohorts. CONCLUSIONS Dose-escalated radiotherapy with ≥ 66Gy for high grade meningioma is associated with improved local control and PFS with an acceptable risk of RN.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".