Neutrophil-to-Lymphocyte Ratio and Platelet-to-Lymphocyte Ratio as Prognostic Markers for Advanced Non-Small-Cell Lung Cancer Treated with Immunotherapy: A Systematic Review and Meta-Analysis
Why this work is in the frame
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Bibliographic record
Abstract
Background and Objectives: Advanced non-small-cell lung cancer (NSCLC) has led to a high number of mortalities. Immunotherapy, as a first-line treatment in advanced NSCLC, currently has no clarity regarding its prognostic markers to assess the treatment outcome. This systematic review aimed to evaluate neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) as prognostic markers in advanced NSCLC patients treated with immunotherapy. Materials and Methods: This systematic review was conducted using the PRISMA guidelines, starting from screening for relevant studies from several databases. Each included cohort study was further assessed by using the Newcastle−Ottawa Quality Assessment Scale, and the available data were extracted for qualitative and quantitative synthesis in pooled and subgroup analysis. Results: A total of 1719 patients were included in this meta-analysis. Hazard ratio (HR) outcomes for progression-free survival (PFS) and overall survival (OS) for NLR and PLR showed significant results, supporting NLR and PLR as prognostic markers (NLR: HR PFS 2.21 [95% CI: 1.50−3.24; p < 0.0001] and HR OS 2.68 [95% CI: 2.24−3.6; p < 0.0001]; PLR: HR PFS 1.57 [95% CI: 1.33−1.84; p < 0.00001] and HR OS 2.14 [95% CI: 1.72−2.67; p < 0.00001]). Subgroup analysis with a cut-off value of 5 for NLR and 200 for PLR also demonstrated notable outcomes. Higher NLR and PLR levels are associated with poor prognostic. Conclusions: There is considerable evidence regarding both markers as prognostic markers in NSCLC patients treated with immunotherapy. However, further studies with more homogeneous baseline characteristics are required to confirm these findings.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.002 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 it