Short Course Hypofractionated Radiotherapy for Frail or Elderly Patients With Meningioma
Bibliographic record
Abstract
Purpose/Objective(s) The incidence of intracranial meningiomas increases with age. The standard of care treatment is complete surgical excision, followed by radiation therapy (RT) if indicated. However, six weeks of RT can be challenging for elderly or frail patients. The purpose of this study was to determine if short course RT is safe and effective in elderly patients with meningioma. Materials/Methods We performed a retrospective analysis of patients with meningioma treated with short course beam RT (5-15 fractions) at a single institution. Seventeen patients (94%) received 4005 cGy over 15 fractions and one patient (6%) received 2500 cGy over five fractions. Study endpoints were treatment toxicity (edema), progression-free (PFS) and overall survival (OS). Results Eighteen patients with histologically proven (n = 12) or radiologically presumed meningioma (n = 6, presumed grade I) were identified. Median age at treatment was 85 years (66-95 years). There were eight, eight and two patients with grade I, II and III tumours, respectively. Eight patients (44%) had radiologic edema prior to RT. Six (33%) required dexamethasone treatment during RT and the dose was increased during RT for two patients. Fourteen patients had reduced or no edema post-RT and 13 patients had stable or improving symptoms post-RT. Six patients had disease progression (five in-field, one out-of-field). Median PFS was 3.3 and 0.9 years for grade I and II/III tumours, respectively (p = 0.014). Median OS was 3.3 and 2.5 years for grade I and II/III tumours, respectively (p = 0.12). Conclusion Short course RT for elderly patients with meningioma is well-tolerated and can offer disease control for some patients, particularly those with grade I tumours.
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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) | 0.001 | 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".