Association of urinary neopterin, neutrophil-to-lymphocyte, lymphocyte-to-monocyte and platelet-to-lymphocyte ratios with long-term survival of patients with breast cancer
Bibliographic record
Abstract
Abstract The immune response crucially determines the survival of patients with malignant tumors including breast carcinoma. The aim of the present study was to evaluate retrospectively an association of peripheral blood cell count (PBC)-derived ratios and urinary neopterin concentration with prognosis in breast cancer patients. Urinary neopterin, neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR) and platelet-to-lymphocyte ratio (PLR) were retrospectively analyzed in a cohort of 474 breast cancer patients. NLR and PLR correlated positively with each other and negatively with LMR, but no correlation between neopterin concentrations and PBC-derived ratios was observed. Increased urinary neopterin concentration was a significant predictor of poor survival in patients with active disease, but PLR, NLR or LMR were not significantly associated with survival in multivariate analysis. In conclusion, increased urinary neopterin was a significant predictor of poor survival in patients with breast cancer and active disease.
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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".