Dietary quality index and the risk of breast cancer: a case-control study
Bibliographic record
Abstract
BACKGROUND: Diet quality is a significant determinant in the etiology of breast cancer (BrCa), but further studies are required to explore this relationship. Therefore, we tried to assess if diet quality, assessed using the Diet Quality Index-International (DQI-I), was related to BrCa among the Iranian population. METHODS: In the present case-control research, 134 women with a recent diagnosis of BrCa and 267 without BrCa were selected as case and control groups. Individual food intake data from a food frequency questionnaire was used to compute DQI-I. Also, the multivariable logistic regression models were utilized to evaluate the association between DQI-I and BrCa odds . RESULTS: We found a significant association between the last tertile of DQI-I and BrCa odds in the fully adjusted model (odds ratio (OR) = 0.30; 95% confidence interval (CI): 0.15-0.56). The subgroup analysis based on menopausal status also showed a significant decrease in BrCa odds in pre-and post-menopausal women (pre-menopausal: OR = 0.27; 95% CI: 0.10-0.70 - post-menopausal status: OR = 0.35; 95% CI: 0.13-0.92). CONCLUSIONS: Our findings indicated that a higher DQI-I score was related to a lower chance of BrCa. According to our research, a healthy diet pattern is crucial for BrCa prevention.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".