Treatment of Older Adult Patients with Glioblastoma: Moving towards the Inclusion of a Comprehensive Geriatric Assessment for Guiding Management
Bibliographic record
Abstract
Glioblastoma (GBM) is the most common primary malignant brain tumor in adults, and over half of patients with newly diagnosed GBM are over the age of 65. Management of glioblastoma in older patients includes maximal safe resection followed by either radiation, chemotherapy, or combined modality treatment. Despite recent advances in the treatment of older patients with GBM, survival is still only approximately 9 months compared to approximately 15 months for the general adult population, suggesting that further research is required to optimize management in the older population. The Comprehensive Geriatric Assessment (CGA) has been shown to have a prognostic and predictive role in the management of older patients with other cancers, and domains of the CGA have demonstrated an association with outcomes in GBM in retrospective studies. Furthermore, the CGA and other geriatric assessment tools are now starting to be prospectively investigated in older GBM populations. This review aims to outline current treatment strategies for older patients with GBM, explore the rationale for inclusion of geriatric assessment in GBM management, and highlight recent data investigating its implementation into practice.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".