Postoperative radiotherapy in subtotally resected recurrent WHO grade 1 meningiomas with intermediate-/high-risk molecular profiles
Bibliographic record
Abstract
BACKGROUND: Meningiomas represent the most common primary intracranial tumors in adults, with World Health Organization (WHO) grade 1 typically associated with favorable outcomes following gross total resection (GTR). METHODS: This retrospective study included patients with CNS WHO grade 1 meningioma and available DNA methylation profiles (n = 210). Clinical tumor characteristics and treatment course (eg, surgical resection, extent of resection, radiotherapy [RT]) were evaluated. Integrated Scores (InS) were calculated based on methylation family using the DKFZ brain tumor classifier, CNS WHO grading, and chromosomal losses, categorized as low, intermediate, or high. Survival analyses employed Kaplan-Meier and Cox regression methods, with local PFS defined as the primary endpoint. RESULTS: In newly diagnosed cases, GTR was associated with a 93.0% 3-year progression-free survival (PFS), compared to 69.3% following subtotal resection (STR). Stratification by IntS showed that patients in the IntS-low group had superior outcomes: 3-year PFS of 93.4 after GTR and 77.4% after STR. In contrast, patients with IntS-intermediate/high profiles showed significantly worse outcomes, with PFS of 85.9% after GTR and 40.0% after STR. Following tumor recurrence, particularly those with IntS-intermediate/high, postoperative RT after STR may improve 3-year PFS to 88.9%, compared to much lower PFS rates in newly diagnosed cases managed without adjuvant RT after STR (3-year PFS: 40.0%). CONCLUSIONS: Our findings highlight the combined impact of both the extent of resection and molecular risk profile on prognosis in newly diagnosed cases. While conservative management is feasible in lower-risk primary cases, recurrent or higher-risk patients may benefit from early postoperative RT.
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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 | 0.000 | 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) | 0.000 | 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".