Potential Impact of Omega 6/3 Ratio and CD68+ Macrophage Infiltration on Survival in NSCLC Patients Undergoing Pulmonary Resection
Bibliographic record
Abstract
Background: Lung cancer remains the leading cause of cancer-related mortality worldwide with non-small cell lung cancer (NSCLC) accounting for the majority of cases. The stage of detection significantly influences survival rates with early-stage diagnosis offering the best prognosis. This study investigates the prognostic impact of the omega-6/omega-3 ratio and tumor infiltration by CD8+ lymphocytes and CD68+ macrophages on overall survival (OS) and disease-free survival (DFS) in NSCLC patients undergoing pulmonary resection. Methods: We conducted a retrospective analysis of 53 patients with early-stage NSCLC who underwent pulmonary resection between September 2017 and January 2020. The omega-6/omega-3 ratio was quantified using gas chromatography and spectrometry. Tumor infiltration by CD8 and CD68 was assessed through immunohistochemistry. Survival outcomes were evaluated using Kaplan-Meier and Cox regression analyses. Results: An increased omega-6/omega-3 ratio and higher CD68+ macrophage infiltration were associated with a trend towards worse OS and DFS in NSCLC patients, though these results did not reach statistical significance. CD8+ T-cell infiltration was associated with improved survival outcomes, confirming its role as a favorable prognostic marker. Comparative analysis with existing datasets revealed similar demographic and clinical characteristics, reinforcing the generalizability of our findings. Conclusions: The omega-6/omega-3 ratio and CD68+ macrophage infiltration serve as important factors potentially influencing prognosis in NSCLC patients undergoing pulmonary resection. These findings highlight the need for further research to refine the prognostic utility of these biomarkers and to explore therapeutic strategies targeting inflammation and immune cell infiltration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".