Mediterranean Diet Patterns in Relation to Lung Cancer Risk: A Meta-Analysis
Bibliographic record
Abstract
Background We systematically quantified the currently inconclusive association between Mediterranean diet patterns and the risk of lung cancer. Methods We searched the PubMed, Cochrane, Database of Abstracts of Reviews of Effects (DARE) and Web of Science electronic databases to identify relevant articles published before October 2021. We used the Newcastle–Ottawa scale to assess the quality of the published research and a random-effects model to estimate the aggregate hazard ratios and 95% CIs. As a result of significant heterogeneity, we performed subgroup analysis, meta-regression analysis, and sensitivity analysis. Where data were available, we also performed a dose–response analysis. Results Nine articles were included in the meta-analysis. The meta-analysis showed that there was a significant negative correlation between Mediterranean diet patterns and the risk of lung cancer in the general population with a hazard ratio of 0.82, a 95% CI of 0.74–0.92, and a high heterogeneity ( I 2 = 59.9%, P < 0.05). As a result of the significant heterogeneity, we conducted subgroup analysis, meta-regression analysis, and sensitivity analysis and found that the study design was the source of the heterogeneity. Subgroup analysis and sensitivity analysis showed that the final results did not change very much, the sensitivity was low and the results were relatively stable. The dose–response relationship showed that, based on the lowest Mediterranean diet score (0 points), for every three-point increase, the risk of lung cancer was reduced by 9%. Conclusion The evidence in this meta-analysis shows that there is a significant negative correlation between Mediterranean diet patterns and the risk of lung cancer, suggesting that Mediterranean diets are a protective factor in lung cancer.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".