Prognostic role of neutrophil to lymphocyte ratio and platelet to lymphocyte ratio in prostate cancer: A meta-analysis of results from multivariate analysis
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: The prognostic role of neutrophil to lymphocyte ratio (NLR) and platelet to lymphocyte ratio (PLR) in patients with prostate cancer (PCa) remains inconsistent. Here we quantify the prognostic impact of these biomarkers and assess their consistency in PCa. MATERIALS AND METHODS: We systematically searched PubMed, Web of Science, and Embase for eligible studies embracing multivariate results. The Newcastle-Ottawa Scale were used to assess the study quality. Pooled hazard ratios (HRs), and 95% confidence intervals (CIs) were calculated. RESULTS: A total of 7228 patients from 18 studies were included in the meta-analysis. Overall, elevated pretreatment NLR was associated with poor overall survival (OS, HR 1.58, 95% CI 1.41-1.78, P < 0.001), progression-free survival (PFS, HR 1.95, 95% CI 1.53-2.49, P < 0.001) and biochemical recurrence-free survival (BRFS, HR 1.37, 95% CI 1.07-1.75, P = 0.011). And high pretreatment PLR was correlated with more inferior PFS (HR 1.62, 95% CI 1.20-2.19, P = 0.002), OS (HR 1.70, 95% CI 1.34-2.15, P < 0.001) and cancer-specific survival (CSS, HR 2.02, 95% CI 1.24-3.29, P = 0.005). Moreover, the subgroup analyses did not alter the direction of results for OS and PFS. CONCLUSION: Based on these findings, elevated NLR and PLR was associated with poor oncologic outcomes, and they can serve as prognostic factors in PCa patients.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it