Impact of glycemia on survival of glioblastoma patients treated with radiation and temozolomide
Bibliographic record
Abstract
Evidence suggests hyperglycemia is associated with worse outcomes in glioblastoma (GB). This study aims to confirm the association between glycemia during radiotherapy (RT) and temozolomide (TMZ) treatment and overall survival (OS) in patients with newly diagnosed GB. This retrospective study included GB patients treated with RT and TMZ from 2004 to 2011, randomly divided into independent derivation and validation datasets. Time-weighted mean (TWM) glucose and dexamethasone dose were collected from start of RT to 4 weeks after RT. Univariate (UVA) and multivariable (MVA) analyses investigated the association of TWM glucose and other prognostic factors with overall survival (OS). In total, 393 patients with median follow-up of 14 months were analyzed. In the derivation set (n = 196) the median OS was 15 months and median TWM glucose was 6.3 mmol/L. For patients with a TWM glucose ≤6.3 and >6.3 mmol/L, median OS was 16 and 13 months, respectively (p = 0.03). On UVA, TWM glucose, TWM dexamethasone, age, extent of surgery, and performance status were associated with OS. On MVA, TWM glucose remained an independent predictor of OS (p = 0.03) along with TWM dexamethasone, age, and surgery. The validation set (n = 197), with similar baseline characteristics, confirmed that TWM glucose ≤6.3 mmol/L was independently associated with longer OS (p = 0.005). This study demonstrates and validates that glycemia is an independent predictor for survival in GB patients treated with RT and TMZ.
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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) | 0.000 | 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".