Dietary Flavonoids and Lung Cancer: A GRADE-Assessed Systematic Review and Meta-Analysis of Observational Studies
Bibliographic record
Abstract
Individual observational studies examining the association between polyphenols and the risk of lung cancer have reported mixed findings. Therefore, we performed a systematic review and meta-analysis to determine the pooled effects between polyphenol intake and lung cancer risk. A systematic search was performed on PubMed, Scopus, and Web of Science databases in April 2023. Random-effect models were used to estimate odd ratios (OR) and 95% confidence intervals (95% CI). In total, 20 studies were included in the systematic review. The pooled analyses indicated that a higher intake of flavonoids (OR = 0.81; 95% CI: 0.67,0.98; p = 0.03) and isoflavone (OR = 0.82; 95% CI: 0.74,0.92; p < 0.001) were associated with lower odds of lung cancer. In addition, the ingestion of anthocyanidin (OR = 0.80; 95% CI: 0.65,0.98; p = 0.04), kaempferol (OR = 0.78; 95% CI: 0.64,0.96; p = 0.02), quercetin (OR = 0.66; 95% CI: 0.48,0.91; p = 0.01) and flavanones (OR = 0.71; 95% CI: 0.59,0.85; p < 0.001) reduced the likelihood of developing lung cancer. Overall, our findings suggest that flavonoids, isoflavones, anthocyanidin, kaempferol, quercetin, and flavanones may protect against 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| 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) | 0.000 | 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".