The prognostic role of neutrophil-to-lymphocyte ratio trends during therapy in esophageal cancer.
Bibliographic record
Abstract
17 Background: Neutrophil-to-lymphocyte ratio (NLR) has been identified as a biomarker for a number of malignancies, with higher ratios being associated with poorer oncologic outcomes. Rather than purely an indicator of advanced disease there is emerging evidence that neutrophils are directly implicated in facilitating cancer progression, and thus alterations and trends of neutrophil counts and NLR during different phases of treatment may reflect a change in oncologic outcome that is as important, or more so, as the absolute count or NLR at baseline. The aim of this study is to investigate the prognostic role of neutrophil-to-lymphocyte ratio trends during the treatment trajectory of patients with esophageal adenocarcinoma. Methods: This is a retrospective study of patients who underwent esophagectomy for esophageal adenocarcinoma between 2005-2016. NLR was measured at three time points: baseline, during neoadjuvant chemotherapy (NAC), and in the late postoperative period. Primary outcomes were overall (OS) and disease-free survival (DFS). Results: 333 patients met our inclusion criteria. Mean age was 65.6 years and 82% of patients were males. The majority of patients had locally advanced disease; 75% had clinical T3 disease and 59% had clinical N-positive disease. NAC was administered in 65.6% of patients. Increasing NLR trends between baseline and late postoperative periods was associated with worse OS (3-year OS 56.1% vs. 71.9%, p=0.045). Patients in the high NLR group before and after treatment did worse than those who moved from high to low groups (3-year OS 42.8% vs. 69.2%, p=<0.0001, 3-year DFS 32.3% vs. 61.8%, p=0.0001). High NLR at baseline and in the postoperative stage is associated with worse OS (3-year OS: 57% vs. 75.7% for baseline and 44.1% vs. 74.9% for postoperative NLR; p=0.0038 and <0.0001, respectively) and DFS (3-year DFS: 52.4% vs. 60.9% for baseline and 34.9% vs. 59.9% for postoperative NLR; p=0.03 and <0.0001, respectively). Patients with complete pathological response to NAC had lower mean baseline NLR (3.2 vs. 4.9 p=0.009). Conclusions: Changes in NLR during treatment may provide a clearer picture about survival outcomes and the role of neutrophils in cancer progression.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".