The prognostic significance of preoperative leukocytosis and neutrophil-to-lymphocyte ratio in patients who underwent radical cystectomy for bladder cancer
Bibliographic record
Abstract
INTRODUCTION: We evaluated the prognostic effects of hematologic parameters of preoperative leukocytosis and neutrophil-to-lymphocyte ratio (NLR) in patients who underwent radical cystectomy for bladder cancer. METHODS: We retrospectively reviewed the medical records of 363 patients who underwent radical cystectomy for bladder cancer between January 1990 and June 2013. In total, 286 patients were included in the study. Age, gender, pathologic stage, lymph node involvement, preoperative hydronephrosis, histologic sub-type, surgical margin status, and lymphovascular invasion were recorded for each patient. Univariate and multivariate analysis were performed to determine the prognostic value of the preoperative clinical and laboratory parameters on disease-specific survival (DSS). Additionally, the correlation between leukocytosis and other factors were evaluated. RESULTS: According to the univariate analysis preoperative leukocytosis and NLR were detected as negative prognostic factors on DSS. Preoperative leukocytosis, NLR, stage, lymph node involvement, histologic subtype, grade and age were independent prognostic factors for DSS, on multivariate analysis. Patients with leukocytosis had higher stage, grade and lymphovascular invasion. CONCLUSIONS: Inexpensive, reproducible, and readily available peripheral blood count components of white blood cell count and NLR were independent prognostic factors, which can stratify DSS risks in bladder cancer patients who underwent radical cystectomy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".