Pretreatment Lymphocyte to Monocyte Ratio as a Prognostic Marker for Advanced Pulmonary Squamous Cell Carcinoma Treated With Chemotherapy
Bibliographic record
Abstract
BACKGROUND: Lower lymphocyte to monocyte ratio (LMR), higher neutrophil to lymphocyte ratio (NLR) and modified Glasgow prognostic score (mGPS) 2 have been demonstrated as independent prognostic markers for poor prognosis of advanced non-small cell lung cancer (NSCLC). However, little is known about these three markers as prognostic markers for a specific histological subset of NSCLC, squamous cell carcinoma (SCC). This study aimed to evaluate the prognostic significance of LMR, NLR and mGPS for advanced SCC. METHODS: We retrospectively collected 107 patients who met the following criteria: pathologically confirmed SCC, chemo-naive patients who had initiated first-line cytotoxic chemotherapy between September 2007 and February 2017 at our institution, and c-stage IIIB, IV or recurrence after curative-intent surgery or thoracic radiotherapy. In order to demonstrate these three markers as significant prognostic factors, we compared overall survival (OS) between two groups divided by LMR, NLR and mGPS 0 - 1 versus 2, and performed univariate and multivariate Cox proportional hazard analyses. RESULTS: Groups with low LMR (< 2.07) and high NLR (≥ 5.28) experienced shorter OS (LMR: 6.5 versus 15.6 months in median, P < 0.01; NLR: 8.2 versus 15.6 months, P < 0.01) than groups with high LMR (≥ 2.07) and low NLR (< 5.28). However, no significant difference was detected in OS between mGPS 0 - 1 and 2 (13.0 versus 13.7 months, P = 0.61). As significant poor prognostic factors, our multivariate Cox hazard analysis detected ECOG PS 2 - 4 (hazard ration (HR): 3.09, 95% confidence interval (CI): 1.77 - 5.40; P < 0.01) and LMR < 2.07 (HR: 0.39, 95% CI: 0.21 - 0.79; P < 0.01). However, NLR was not selected in the multivariate analysis. CONCLUSION: LMR is an independent prognostic factor for advanced pulmonary SCC. Neither NLR nor mGPS is useful as prognostic factor for this histology. The optimal prognostic markers may differ from each subset of NSCLC.
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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".