Prognostic factors for overall survival in elderly patients with glioblastoma: Analysis of the pooled NOA-08 and Nordic trials with the CCTG-EORTC (CE.6) trial
Bibliographic record
Abstract
Abstract Background The majority of patients diagnosed with glioblastoma are >60 years. Three randomized trials addressed the roles of radiotherapy (RT) and temozolomide (TMZ) for elderly patients. NORDIC and NOA-08 compared RT versus TMZ, while CE.6 randomized between hypofractionated RT and RT + TMZ. All showed significant benefits for the TMZ arms, especially for those patients with O6-methylguanine DNA methyltransferase (MGMT) promoter-methylated tumors. This pooled analysis aimed at identifying additional factors that could improve individualized treatment recommendations. Methods Analyses were performed separately in the RT and TMZ arms of the pooled NORDIC and NOA-08 data, and in the RT and TMZ/RT arms of CE.6. The prognostic value of baseline clinical factors, comorbidities, and quality of life (QoL) scores were assessed. Results NORDIC + NOA-08 (NN) included 715 patients and CE.6 included 562 patients. Median age for NN was 71 and 73 years for CE.6. In NN and CE.6 respectively, 66.2% versus 70.5% underwent resection and 50.9% and 75.3% were on steroids. In NN, 401 patients received RT alone and 281 in CE.6, while 314 were randomized to TMZ alone in NN and 281 to concomitant RT + TMZ in CE.6. Known clinical prognostic factors, such as extent of resection and WHO performance status were confirmed, as was MGMT promoter methylation status for TMZ-treated patients. TMZ-treated patients with 2 or 3 comorbidities; hypertension, diabetes, and/or stroke had worse survival, both in NN (P = .022) and CE.6 (P = .022). Baseline QoL had a minor association with outcome. Conclusion Consideration of comorbidities allows improved personalized treatment decisions for elderly glioblastoma 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 | 0.011 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.011 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".