A large-scale case-control study on the association between dietary fat quality indices and risk of breast cancer
Bibliographic record
Abstract
The relationship between breast cancer (BC) and total dietary and types of fat is well-established, however, the association with dietary fat quality (DFQ) indices remains to be elucidated. Therefore, the aim was to investigate the associations between DFQ indices and odds of BC among women. This hospital-based case-control study included 464 women with pathologically confirmed BC during the past year and 498 apparently healthy controls of similar age and residence. Dietary intake was assessed using a validated food frequency questionnaire (FFQ) and DFQ indices were calculated. The likelihood of BC was evaluated across tertiles of specific DFQ indices scores [atherogenicity index (AI), thrombogenic index (TI), hypo- and hypercholesterolemic fatty acids ratio (h/H), omega-3 to omega-6 polyunsaturated fatty acids ratio (∑ω-3/∑ω-6), polyunsaturated fatty acids/saturated fatty acids ratio (PSR), dietary lipophilic index (LI), cholesterol/saturated fat index (CSI)]. After controlling for several potential confounders, CSI was inversely associated with BC risk among all participants (OR: 0.53, 95% CI: 0.37-0.76; P = 0.001). This association remained significant after stratified analysis in pre-postmenopausal women. In addition, there were higher odds of BC in the highest category of PSR compared to the lowest category in among postmenopausal women (OR: 1.93; 95% CI: 1.07-3.48 P = 0.03). There were no other significant associations between BC risk and the other DFQ indices.PSR and CSI might be directly and inversely associated with the odds of BC, respectively. To confirm the causality of the associations, prospective cohort studies are needed.
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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 | 0.002 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".