PRECISION THROUGH MODERATION: REDEFINING GBM THERAPY IN THE ELDERLY WITH HYPOFRACTIONATED RADIOTHERAPY
Bibliographic record
Abstract
Background: Glioblastoma (GBM) is the most aggressive primary brain tumor, with particularly poor prognosis in elderly patients due to age-related comorbidities and reduced treatment tolerance. Standard therapy based on the Stupp protocol is often poorly suited to this population. Hypofractionated radiotherapy (HFRT) has emerged as a promising alternative, but optimal regimens and outcomes remain under investigation. This prospectiv Methods: e single-arm study included 25 patients aged ≥60 years with histologically confirmed GBM and Karnofsky Performance Status (KPS) >50. All patients underwent maximal safe resection followed by HFRT (40.05 Gy in 15 fractions) with concurrent temozolomide (TMZ) and adjuvant TMZ per the Stupp protocol. The primary endpoint was overall survival (OS); secondary endpoints included progression-free survival (PFS), treatment compliance, toxicity, and neurologic outcomes. The median age was 63.7 years. Gross total resection was achieved in 84% of patients. Adju Results: vant TMZ was administered in 76%. Median OS and PFS were 7.99 and 5.69 months, respectively. Extent of resection significantly influenced PFS (p = 0.028), but not OS. Treatment was well tolerated, with no grade 3–4 hematologic toxicity. Posttreatment neurologic improvement was noted in 44% of patients, with stable or improved KPS in 80%. Mild cognitive decline occurred in 20% of patients. HFRT combined with TMZ is a feasible, effective, and well-toler Conclusion: ated treatment option for elderly GBM patients. It provides survival outcomes comparable to conventional regimens with improved tolerability and functional preservation. These findings support HFRT as a standard approach in appropriately selected elderly or frail patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 teacher head, 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".