Prognostic Utility of Neutrophil-to-Lymphocyte Ratio in Patients with Metastatic Colorectal Cancer Treated Using Different Modalities
Bibliographic record
Abstract
Introduction: Inflammation is a critical component in carcinogenesis. The neutrophil-to-lymphocyte ratio (nlr) has been retrospectively studied as a biomarker of prognosis in metastatic colorectal cancer (mcrc). Compared with a low nlr, a high nlr is associated with worse prognosis. In the present study, we compared real-world survival for patients with mcrc based on their nlr group, and we assessed the utility of the nlr in determining first-line chemotherapy and metastasectomy benefit. Methods: In this retrospective and descriptive analysis of patients with mcrc undergoing first-line chemotherapy in a single centre, the last systemic absolute neutrophil and lymphocyte count before treatment was used for the nlr. A receiver operating characteristic curve was used to estimate the nlr cut-off value, dividing the patients into low and high nlr groups. Median overall survival (mos) was compared using Kaplan–Meier curves and the log-rank test. A multivariate analysis was performed using a Cox regression model. Results: The 102 analyzed patients had a median follow-up of 15 months. Regardless of systemic therapy, approximately 20% of patients underwent metastasectomy. The nlr cut-off was established at 2.35, placing 45 patients in the low-risk group (nlr < 2.35) and 57 in the high-risk group (nlr ≥ 2.35). The Kaplan–Meier analysis showed a mos of 39.1 months in the low-risk group and 14.4 months in the high-risk group (p < 0.001). Multivariate Cox regression on the nlr estimated a hazard ratio of 3.08 (p = 0.01). Survival analysis in each risk subgroup, considering the history of metastasectomy, was also performed. In the low-risk group, mos was longer for patients undergoing metastasectomy than for those not undergoing the procedure (95.2 months vs. 22.6 months, p = 0.05). In the high-risk group, mos was not statistically different for patients undergoing or not undergoing metastasectomy (24.3 months vs. 12.7 months, p = 0.08). Conclusions: Our real-world data analysis of nlr in patients with mcrc confirmed that this biomarker is useful in predicting survival. It also suggests that nlr is an effective tool to choose first-line treatment and to predict the benefit of metastasectomy.
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How this classification was reachedexpand
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 | 0.000 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".