QOL-22. Prognostic associations of the G8 geriatric screening tool in the EORTC Brain Tumor Group trials 1608 and 1709 in newly diagnosed glioblastoma
Bibliographic record
Abstract
Abstract BACKGROUND The G8 screening assessment tool has been validated to assess frailty risk in older patients with cancer. A score of 14 or less is considered to identify patients at risk of frailty. The G8 has been implemented for all EORTC clinical trials including patients 70 years or older since 2017. Here we assessed the prognostic value of the G8 at baseline in older patients with newly diagnosed glioblastoma enrolled in clinical trials. MATERIAL AND METHODS Data from 83 patients aged 70 or older enrolled in the 1608 STEAM trial (NCT 03224104) (n=20) or the 1709 MIRAGE trial (NCT 03345095) (n=63) were analyzed. We defined a G8 low (≤14) and a G8 high group (15-17). RESULTS The median age was 73 years, 29 patients (34.9 %) were female, 54 patients (65.1 %) were male. The KPS was 90 or more in 42 patients (50.6 %). Steroids were taken at baseline by 33 patients (39.8 %). 38 patients (45.8 %) were assigned to the G8 low group, and 45 patients (54.2 %) to the G8 high group. Patients with a KPS of 90 or 100 were more often in the G8 high group (adjusted OR = 6.98, 95% CI 2.19 – 25.64). Patients in the G8 high group had higher means for global health status scale and functioning scores at baseline than patients in the G8 low group. Treatment delivery measured by the relative dose intensity was better in patients with a high G8 than in patients with a low G8 (OR = 2.26, 95% CI 0.81- 6.53). Patients in the G8 low group tended to experience more toxicity than patients in the G8 high group. Patients in the G8 high group had a longer progression-free (adjusted HR = 0.37, 95% CI 0.20 – 0.68, p=0.0013) and overall survival (adjusted HR = 0.40, 95% CI 0.21 – 0.75, p=0.0045). CONCLUSION The G8 score may be a powerful tool for prognostic assessment and for patient stratification in old patients with glioblastoma.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".