Correlation between Lymphocyte-to-Monocyte Ratio (LMR), Neutrophil-to-Lymphocyte Ratio (NLR), Platelet-to-Lymphocyte Ratio (PLR) and Extramural Vascular Invasion (EMVI) in Locally Advanced Rectal Cancer
Bibliographic record
Abstract
Rectal cancer constitutes around one-third of all colorectal cancers. New markers are required to optimize the treatment. Extramural vascular invasion (EMVI) is a magnetic resonance imaging (MRI)-based negative prognostic marker. Lymphocyte-to-monocyte ratio (LMR), neutrophil-to-lymphocyte ratio (NLR) or platelet-to-lymphocyte ratio (PLR) are blood-based systemic inflammatory response markers with proven prognostic value in many cancers, including CRC. We hypothesized whether there is a relationship between LMR, NLR, PLR and the presence of EMVI on pre-treatment MRI in patients with locally advanced rectal cancer (LARC). We conducted a retrospective analysis of 371 patients with LARC treated in the Maria Skłodowska-Curie National Research Institute of Oncology, Warsaw, Poland between August 2016 and December 2021. One hundred eighty-four patients were found eligible for the study. A correlation between the extension of the tumour, nodal status, clinical stage of the disease and the presence of EMVI was found (p < 0.001). The pre-treatment level of neutrophils, platelets and carcinoembryonic antigen (CEA) was significantly higher in the EMVI-positive population (p = 0.041, p = 0.01, p = 0.027, respectively). There were no significant differences regarding the level of LMR, NLR and PLR between the EMVI-positive and EMVI-negative population. LMR, NLR and PLR do not differentiate patients in terms of EMVI; neither of these parameters is a good predictor of the status of EMVI in LARC.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".