The platelets-neutrophils to lymphocytes ratio: a new prognostic marker in metastatic colorectal cancer
Bibliographic record
Abstract
Background: The cancer micro-environment is recognized as having an increasing importance in cancer progression. Immune cells originating from the peripheral blood are important elements of this environment. Thrombocytosis, neutrophilia and lymphocytopenia have been found to be negative prognostic indicators in many cancers. This study aims to evaluate the potential of the use of a novel hematological marker, the platelet-neutrophil to lymphocyte ratio (PNLR) as a practical, reliable, and inexpensive prognostic tool in metastatic colorectal adenocarcinomas. Methods: Charts from 305 patients with colorectal cancer were retrospectively reviewed. Of these, 152 had metastatic disease with complete follow-up data on progression and survival. Data were extracted and stratified by a PNLR cut-off point of 2,000. Baseline parameters of the two groups were evaluated and compared with the χ2 test. Univariate and multivariate Cox proportional-hazards regression analyses were performed on variables of interest. Results: A total of 102 (67.1%) patients had a PNLR of less than 2,000 while the index for 50 (32.9%) patients was 2,000 or higher. Patients with a PNLR above 2,000 had a shorter median progression-free survival (PFS) [6.5 vs. 13.3 months; hazard ratio (HR), 2.05; 95% CI, 1.32–3.19, P=0.001] than in patients with a PNLR below the threshold. Similar results were observed for median overall survival (OS) (9.6 vs. 21.8 months; HR, 2.33; 95% CI, 1.44–3.79, P=0.001). PNLR had a higher predictive HR than Eastern Cooperative Oncology Group (ECOG) performance status (PS). Conclusions: In this retrospective analysis of metastatic colorectal cancer patients, PNLR had prognostic value for both OS and PFS. While other variables held significance for poorer prognosis, PNLR had the highest HR and the highest significance in multivariate analysis for both PFS and OS. Thus, it represents a powerful and objective prognostic tool in the evaluation of metastatic colorectal cancer patients that is readily available and does not require any additional expenses.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".