Dietary B-Vitamin Intake and Risk of Breast, Endometrial, Ovarian and Colorectal Cancer among Canadians
Bibliographic record
Abstract
Few studies have explored the associations of thiamin, niacin and riboflavin with risk of cancer despite their role in potentially cancer-associated one-carbon metabolism. Using multivariable Cox proportional hazards regression models modified for the case-cohort design, we examined the associations of dietary intake of the above-mentioned B vitamins, as well as folate, and vitamins B6 and B12, with risk of the breast (n = 922), endometrial (n = 180), ovarian (n = 104) and colorectal (n = 266) cancers among age-stratified subcohorts of 3,185 women who were randomly selected from a cohort of 73,909 participants. None of the B-vitamins were associated with risk of breast or colorectal cancers. However, relatively high dietary intake of folate intake was inversely associated with risk of endometrial (HRq4 vs q1: 0.52; 95% CI: 0.29–0.93) and ovarian (HRq3 vs q1: 0.39; 95% CI: 0.19–0.80) cancers while relatively high dietary intake of vitamin B6 was inversely associated with ovarian cancer risk (HRq3 vs q1: 0.49; 95% CI: 0.24–0.98). These findings suggest that dietary intake of folate may reduce risk of endometrial and ovarian cancers and dietary intake of vitamin B6 may reduce risk of ovarian cancer.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".