Prognostic role of neutrophil to lymphocyte ratio in lung cancers: a meta-analysis including 7,054 patients
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Bibliographic record
Abstract
BACKGROUND: Neutrophil to lymphocyte ratio (NLR) has recently been reported to be a poor prognostic indicator in lung cancer. However, the prognostic value of the NLR in patients with lung cancer still remains controversial. We performed a meta-analysis to evaluate the prognostic value of NLR in patients with lung cancer. METHODS: We performed a comprehensive literature search in PubMed, Ovid, the Cochrane Library, and Web of Science databases in May 2015. Studies were assessed for quality using the Newcastle-Ottawa Scale. RESULTS: Twenty-two studies with a total of 7,054 patients were included in this meta-analysis. The meta-analysis was performed to generate combined hazard ratios (HRs) for overall survival (OS) and progression-free survival (PFS). Our analysis results indicated that high NLR predicted poorer OS (HR, 1.51; 95% confidence interval [CI], 1.33-1.71; P<0.001) and PFS (HR, 1.33; 95% CI, 1.07-1.67; P=0.012) in patients with lung cancer. High NLR was also associated with poor OS in lung cancer treated by surgical resection (HR, 1.59; 95% CI, 1.26-1.99; P<0.001) and chemotherapy (HR, 1.15; 95% CI, 1.08-1.22; P<0.001). In addition, NLR cut-off value =5 (HR, 1.57; 95% CI, 1.16-2.12; P=0.003) and NLR cut-off value <5 (HR, 1.47; 95% CI, 1.28-1.69; P<0.001). CONCLUSION: This meta-analysis result suggested that NLR should have significant predictive ability for estimating OS and PFS in patients with lung cancer and may be as a significant biomarker in the prognosis of lung cancer.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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