The Mediating Role of Oxidative Stress on the Association Between Oxidative Balance Score and Cancer-Related Cognitive Impairment in Lung Cancer Patients: A Cross-Sectional Study
Bibliographic record
Abstract
Objectives: To explore the association between the oxidative balance score (OBS) and cancer-related cognitive impairment (CRCI) in patients with lung cancer, as well as the oxidative stress biomarkers involved. Methods: In this cross-sectional study, 315 lung cancer patients were recruited, from whom 142 blood samples were collected to determine oxidative stress biomarkers. Dietary intake was assessed using 3-day, 24 h dietary recalls. The OBS was calculated by summing up pro- and antioxidant factors from a diet and lifestyles assessment. CRCI was evaluated using the Montreal Cognitive Assessment (MoCA) test. Results: A total of 103 patients (32.7%) developed CRCI, with significantly lower OBS and dietary OBS and lower superoxide dismutase (SOD) and glutathione peroxidase (GPx) activities than non-CRCI patients (p < 0.05). For every 1-point increase in OBS, the risk of CRCI was reduced by 10.6% (OR = 0.894; 95% CI 0.819, 0.977; p = 0.013). Both vitamin E (OR = 0.922; 95% CI 0.868, 0.980; p = 0.009) and dietary fiber (OR = 0.909; 95% CI 0.832, 0.992; p = 0.032) were significantly inversely related to CRCI. The association between the total OBS and CRCI was mediated by SOD (ACME = −0.0061; 95% CI −0.0170, −0.0004; p = 0.015) and GPx (ACME = −0.0069; 95% CI −0.0203, −0.0002; p = 0.032), respectively. Conclusions: Lung cancer patients with a greater balance of antioxidant to pro-oxidant diet, especially rich in dietary fiber and vitamin E, may decrease their CRCI in part by affecting SOD and GPx activities.
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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 | 0.001 |
| 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 | 0.001 | 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".