B-Vitamin Intake, One-Carbon Metabolism, and Survival in a Population-Based Study of Women with Breast Cancer
Bibliographic record
Abstract
Breast cancer is the second leading cause of cancer mortality among women. Given its important role in DNA methylation and synthesis, one-carbon metabolism may affect breast cancer mortality. We used a population-based cohort of 1,508 women with breast cancer to investigate possible associations of dietary intake of B vitamins before diagnosis as well as nine polymorphisms of one-carbon metabolizing genes and subsequent survival. Women newly diagnosed with a first primary breast cancer in 1996 to 1997 were followed for vital status for an average of 5.6 years. Kaplan-Meier survival and Cox proportional hazard regression analyses were used to evaluate the association between dietary intakes of B vitamins (1,479 cases), genotypes ( approximately 1,065 cases), and all-cause as well as breast cancer-specific mortality. We found that higher dietary intake of vitamin B(1) and B(3) was associated with improved survival during the follow-up period (P(trend) = 0.01 and 0.04, respectively). Compared with the major genotype, the MTHFR 677 T allele carriers have reduced all-cause mortality and breast cancer-specific mortality in a dominant model [hazard ratio (95% confidence interval): 0.69 (0.49-0.98) and 0.58 (0.38-0.89), respectively]. The BHMT 742 A allele was also associated with reduced all-cause mortality [hazard ratio, 0.70 (0.50-1.00)]. Estrogen receptor/progesterone receptor status modified the association between the MTHFR C677T polymorphism and survival (P = 0.05). The survival associations with one-carbon polymorphisms did not differ with the use of chemotherapy, although study power was limited for examining such effect modification. Our results indicate that one-carbon metabolism may be an important pathway that could be targeted to improve breast cancer survival.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".