Baseline neutrophil to lymphocyte ratio as a prognostic marker for patients with muscle-invasive bladder cancer being treated with neoadjuvant chemotherapy.
Bibliographic record
Abstract
468 Background: The neutrophil-to-lymphocyte ratio (NLR), an inflammatory marker, has been associated with a poor prognosis in several solid malignancies. In muscle-invasive bladder cancer (MIBC), an elevated pre-cystectomy NLR has been shown to predict for poor survival; however, its role in prognostication for patients being treated with neoadjuvant chemotherapy (NAC) is unknown. We evaluated the baseline NLR as an independent prognostic factor in patients with MIBC treated with NAC. Methods: Patients with MIBC treated with NAC in Alberta from 2005 to 2015, and at the Princess Margaret Hospital in Ontario from 2005 to 2013 were evaluated. All 290 patients treated with NAC were included; 272 were evaluable for NLR and outcomes. Patient, disease, and treatment-related factors were evaluated. NLR was examined prior to initiation of preoperative chemotherapy. The prognostic role of NLR on overall survival (OS) and progression-free survival (PFS) was determined using Cox proportional hazard regression analysis. Results: The median age of patients was 66 years (range 36-87). The majority of patients (77%) were male. Median baseline NLR at diagnosis was 2.9. NLR > 3.0 at baseline was independently associated with PFS and OS after adjustment for age, gender and stage (Table). Patients with an NLR > 3 had a median PFS of 14.1 months compared to 25.1 months in those patients with a baseline NLR ≤ 3 (HR 0.63, p = 0.01). Similarly, OS was 19.4 months in patients with a baseline NLR > 3 compared to 33.4 months in those with a baseline NLR ≤ 3 (HR 0.65, p = 0.04). Conclusions: NLR is an independent prognostic factor for patients with MIBC undergoing NAC. [Table: see text]
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".