The Prognostic Impact of Neutrophil Lymphocytic Ratio (NLR) on Survival of Patients with Glioblastoma Multiforme (GBM): A Retrospective Cohort Study
Bibliographic record
Abstract
Background and aim: Neoplasia related inflammation now is proved to be a factor determining the outcomes in patients with cancer including glioblastoma, we aimed to determine the prognostic value of NLR on the progression free (PFS) and overall survival (OS) for patients with GBM.Methods: The baseline complete blood picture prior to the initiation of any corticosteroid and cancer therapy (surgery and RT) was obtained then NLR was determined and correlated with PFS and OS for patients with GBM.Results: patients with NLR ≤4 had a significantly better PFS (the median PFS=12±1.614 months, CI=8.836-15.164 for those with NLR ≤4 vs. a Median PFS=6±1.239 months, CI=3.572-8.428 for those with NLR>4, P<0.009) and OS (the median OS=15±3.627 months, CI=7.890-22.110 vs. a median OS=7±1.038 months, CI=4.966-9.034, P<0.002 for those with NLR≤4 vs. those with NLR>4 respectively). And this effect of NLR was dependant on other prognostic factors.Conclusion: NLR had a prognostic effect on PFS and OS, but it wasn't an independent factor for survival.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".