Glioblastoma in the elderly: making sense of the evidence
Bibliographic record
Abstract
Abstract Glioblastoma is a highly malignant neoplasm, notorious for its poor prognosis. The median age of diagnosis is 64 years, with an increasing number of patients diagnosed over the age of seventy. Managing elderly patients with this condition is challenging. Management pathways may include surgery, radiotherapy, chemotherapy, and best supportive care. Many clinical trials in oncology exclude elderly patients, including some of those for malignant brain tumors, leaving less evidence to guide treatment in these patients. Recent advances in molecular diagnostics and biomarkers, such as 06-methylguanine-DNA-methyltransferase (MGMT) promoter methylation status, may help guide optimal treatment selection. Focusing on available randomized data, this review provides a practical overview of the evidence for treating newly diagnosed glioblastoma in the elderly, including management recommendations.
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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 | 0.001 | 0.010 |
| 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 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".