A Randomized Double-Blind Placebo-Controlled Trial of the Effect of Vitamin D3 Supplementation on Breast Density in Premenopausal Women
Bibliographic record
Abstract
Abstract Background: This double-blind, placebo-controlled parallel group trial assessed whether oral supplementation with 1,000, 2,000, or 3,000 IU/day vitamin D3 over one year reduces percent mammographic breast density in premenopausal women. Methods: The trial was conducted between October 2012 and June 2015, among premenopausal female volunteers from Quebec City (Quebec, Canada). Women were randomized with ratio 1:1:1:1 to one of four study arms (1,000, 2,000, or 3,000 IU/day vitamin D3 or placebo). The primary outcome was mean change in percent mammographic breast density. Participants and research team were blinded to study arm assignment. Results: Participants (n = 405) were randomized to receive 1,000 (n = 101), 2,000 (n = 104), or 3,000 IU/day (n = 101) vitamin D3, or a placebo (n = 99). The primary analysis included 391 participants (96, 99, 100, and 96, respectively). After the one-year intervention, mean ± SE change in percent breast density in the arms 1,000 IU/day (–5.5% ± 0.5%) and 2,000 IU/day (–5.9% ± 0.5%) vitamin D3 was similar to that in the placebo arm (−5.7% ± 0.5%) (P values = 1.0). In the 3,000 IU/day vitamin D3 arm, percent breast density also declined but slightly less (–3.8% ± 0.5%) compared with placebo arm (P = 0.03). Adherence to intervention was excellent (92.8%), and reporting of health problems was comparable among study arms (P ≥ 0.95). All participants had normal serum calcium. Conclusions: In premenopausal women, one-year supplementation with 1,000, 2,000, or 3,000 IU/day vitamin D3 resulted in a reduction of percent breast density no greater than that seen with the placebo. Impact: At doses of 1,000–3,000 IU/day, vitamin D supplementation will not reduce breast cancer risk through changes in breast density. Cancer Epidemiol Biomarkers Prev; 26(8); 1233–41. ©2017 AACR.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".