A Prospective Analysis of Plasma Phospholipid Fatty Acids and Breast Cancer Risk in 2 Provinces in Canada
Bibliographic record
Abstract
Studies suggest that fatty acid status influences breast cancer etiology, yet the roles of individual fatty acids in breast cancer risk are unclear, specifically when central adiposity and menopausal status are considered. This study examined the associations of fatty acid status with breast cancer risk including location, menopausal status, and waist-to-hip ratio as key variables. Prediagnostic plasma phospholipid fatty acids were measured in women with breast cancer (n = 393) and age-matched controls (n = 786) from a nested case-control prospective study within Alberta’s Tomorrow Project (ATP) and British Columbia Generations Project (BCGP) cohorts. Binary logistic regression models were used to evaluate associations of fatty acids and breast cancer risk with subgroup analysis for menopausal status and waist-to-hip ratio. Women from BCGP had a higher n–3 (ɷ-3) fatty acid status compared with the ATP (6.4% ± 0.08% vs. 5.3% ± 0.06%; P < 0.001), so subsequent analysis was blocked by cohort. Overall, fatty acids had inconsistent associations with risk. In the ATP among premenopausal women, total long-chain n–3 fatty acids (ORQ4vsQ1 = 1.78; 95% CI: 0.58, 5.43; P-trend = 0.007, P-interaction = 0.07) were positively associated with breast cancer risk, whereas in BCGP, DHA (ORQ4vsQ1 = 0.66; 95% CI: 0.28, 1.53; P-trend = 0.03, P-interaction = 0.05) and total long-chain n–3 fatty acids (ORQ4vsQ1 = 0.66; 95% CI: 0.28, 1.54; P-trend = 0.03) were associated with decreased cancer risk when the waist-to-hip ratio was <0.85. Our findings suggest that regional variations in fatty acid status influence breast cancer risk, resulting in positive associations of total long-chain n–3 fatty acids in premenopausal ATP women and negative associations of these fatty acids in BCGP women with a waist-to-hip ratio below guidelines. This study highlights the complexity and difficulty in using fatty acid status to predict breast cancer risk in diverse populations without the consideration of other risk factors.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".