Impact of lymphopenia on survival for elderly patients with glioblastoma: A secondary analysis of the CCTG CE.6 (EORTC 26062-22061, TROG03.01) randomized clinical trial.
Bibliographic record
Abstract
2547 Background: Lymphopenia (LMP) may lead to worse outcomes for patients with glioblastoma (GBM). This study is a secondary analysis of the CCTG CE.6 trial evaluating the impact of chemotherapy and radiation on LMP, as well as the association of LMP with overall survival. Methods: CCTG clinical trial CE.6 randomized elderly GBM patients (≥ 65 yrs) to short course radiation alone (RT) or short course radiation with temozolomide (RT + TMZ). In this study LMP (mild-mod: grade 1-2; severe: grade 3-4) was defined per CTCAE v3.0 criteria, and measured at baseline, 1 wk and 4 wks post-RT. Pre-selected key factors for the analysis included age, sex, ECOG, extent of resection, MGMT methylation, MMSE, and steroid use. Multinomial logistic regression models were used to identify factors associated with LMP and multivariable Cox regression models were used to study effect of LMP on survival. Results: A total of 562 patients were included for analysis (281 RT vs 281 RT+TMZ). At baseline, both arms (RT vs RT+TMZ) had similar rates of mild-mod (21.4% vs 21.4%) and severe (3.2% vs 2.9%) LMP. The 1 wk post-RT LMP rates were also similar (p = 0.25). However, RT+TMZ pts were more likely to develop both mild-mod LMP (18.2% vs 27.9%) and severe LMP (1.8% vs 9.3%) [p < 0.001] at 4 wks post-RT. Developing mild-mod and severe LMP post-RT were both associated with baseline LMP (p < 0.001) and RT+TMZ (p < 0.001). Severe LMP at 4 wks post-RT was also associated with biopsy only (p < 0.02). After adjusting for confounding factors, 4 wks post-RT LMP was not significantly associated with PFS or OS regardless of severity. However, baseline LMP (HR 1.3) was significantly associated with worse OS (HR: 1.30, 95% C.I.: 1.05-1.62, p = 0.02), regardless of MGMT status. Other factors significantly associated with worse outcome included: males (HR 1.41), biopsy only (HR 1.59), and lower MMSE (HR 1.03). Conclusions: Short course RT alone does not lead to LMP after treatment. Development of LMP post-RT is associated with addition of TMZ and baseline LMP. However, only baseline LMP is associated with worse OS regardless of MGMT status. This may be considered as a prognostic biomarker for elderly GBM patients and warrants further validation. Clinical trial information: NCT00482677 .
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".