Vitamin D and Calcium Supplement Use and High-Risk Breast Cancer: A Case–Control Study among BRCA1 and BRCA2 Mutation Carriers
Bibliographic record
Abstract
The role of vitamin D and calcium use in the development of breast cancer among women in the general population is not clear. Furthermore, whether vitamin D and calcium supplement use are associated with breast cancer in high-risk populations has not been evaluated. Thus, we evaluated the association between vitamin D and/or calcium supplement use and breast cancer among women with a pathogenic variant (mutation) in BRCA1 or BRCA2. BRCA mutation carriers enrolled in a longitudinal study were invited to complete a supplemental questionnaire on lifetime supplement use. Cases included women with a prevalent diagnosis of invasive breast cancer, and controls had no history of breast cancer. Vitamin D and calcium use were categorized as never/ever use, and as tertiles of supplement intake (total average daily supplement use). Unconditional logistic regression was used to estimate the odds ratio (OR) and 95% confidence intervals (CIs) of breast cancer. This study included 134 breast cancer cases and 276 controls. Women who used vitamin D-containing supplements had 46% lower odds of having breast cancer compared to those who never used supplements (OR 0.54; 95% CI 0.31, 0.91; p = 0.02). Increasing vitamin D and calcium supplement intake was inversely associated with the odds of having breast cancer (p-trend = 0.04). Findings were suggestively stronger among BRCA1 mutation carriers; however, analyses were limited by small strata. These findings suggest a potential inverse association between vitamin D and calcium supplementation and BRCA breast cancer. Additional studies are warranted to confirm these findings and accurately inform clinical care guidelines.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".