Glioblastoma in the elderly: initial management
Bibliographic record
Abstract
Glioblastoma is the most common primary CNS malignancy and it is becoming more frequently diagnosed in the elderly population. Glioblastoma is associated with a dismal prognosis and remains a huge challenge for the neuro-oncology community. Surgical resection/biopsy is well defined as an important first approach in the care of this disease, for tumor diagnosis, molecular analysis and maximum resection. MGMT promoter methylation status has proved to be a useful indicator of whether single modality (RT or TMZ alone) or combined modality treatment may achieve better outcomes. Post-operative treatment options include: (I) hypofractionated radiotherapy (HRT) with concurrent and adjuvant temozolomide (TMZ) or (II) HRT alone (MGMT unmethylated patients); (III) TMZ alone (MGMT methylated patients) when combined modality is not feasible due to patient poor performance status or multiple comorbidities. Following the positive survival outcomes of the CCTG CE.6/EORTC 26062-22061 phase III trial which randomized newly diagnosed glioblastoma patients aged 65 or older to HRT (40 Gy/15 fractions) with concurrent and adjuvant temozolomide to HRT alone, combined modality therapy (CMT) with HRT with concurrent temozolomide as the initial post-surgical approach should be considered in patients well enough to have treatment. In meantime, future trials addressing new approaches are needed to improve outcomes in this fatal disease.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".