Glioblastoma Treatment in the Elderly in the Temozolomide Therapy Era
Bibliographic record
Abstract
BACKGROUND: optimal treatment of glioblastoma (gBM) in the elderly remains unclear. the impact of age on treatment planning, toxicity, and efficacy at a Canadian Cancer Centre was retrospectively reviewed. METHODS: glioblastoma patients treated consecutively between 2004 and 2008 were reviewed. utilizing 70 years as the threshold for definition of an elderly patient, treatments and outcome were compared in younger and elderly populations. RESULTS: four hundred and twenty one patients were included in this analysis and median overall survival (oS) for the entire cohort was 9.8 months. 290 patients were aged <70 (median age 57, range 17- 69) and 131 were aged ≥ 70 (median age 76, range 70-93). patients ≥ 70 were more likely to receive best supportive care (BSC) and all patients >70 who were treated with radiotherapy received <60 gy (P<0.001), except one. patients aged >70 demonstrated inferior survival (one year oS 16% versus 54% for those <70, hr 3.46, P<0.001). in patients treated with BSC only, age had no impact on survival (median survival two months in both groups, hr 0.89, P=0.75). for those treated with higher doses of radiotherapy (>30 gy to <60 gy), one year survival was 19% versus 24% in patients aged >70 versus <70 (hr 1.47, P=0.02) respectively. CONCLUSION: in this retrospective single institution series, elderly patients were more likely to be treated with BSC or palliative doses of radiotherapy. randomized phase iii study results are required for guidance in treatment of this population of patients.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".