Adherence to a western dietary pattern and risk of invasive ductal and lobular breast carcinomas: a case–control study
Bibliographic record
Abstract
Little is known about the role of diet in the risk of invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC) of the breast, the most common histological subtypes of breast cancer (BC). This is because, the majority of studies on the association of diet and the risk of BC are focused on single food items, and studies considering the overall diet in terms of dietary patterns are limited. Also, the potential heterogeneity in the impact of Western diet (WD) on histological subtypes of BC is not established. This, the age-frequency-matched case-control study included 1009 incident BC cases and 1009 healthy controls. The required data was obtained from the patients' medical files and interviews using a previously validated researcher-designed questionnaire for collecting data on socio-economic and anthropometric statuses and a valid food frequency questionnaire (FFQ) to measure the participants' dietary intake. We used multinomial logistic regression, and odds ratios (ORs) with 95% confidence intervals (CIs) were calculated. A positive and significant association was observed between higher adherence to a WD and risk of IDC (OR comparing highest with the lowest tertile: 2.45, 95% CI 1.88, 3.17; p-trend < 0.001), whereas no significant association was observed between adherence to the WD and the risk of ILC (OR comparing highest with the lowest tertile: 1.63, 95% CI 0.63, 3.25) (p for heterogeneity = 0.03). The results of an analysis stratified by menopausal status suggested a similar pattern. We provided evidence that adherence to a WD raises the risk of IDC, but not ILC, suggesting different etiological mechanisms for IDC and ILC.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".