Vitamin D Supplementation and Breast Cancer Prevention: A Systematic Review and Meta-Analysis of Randomized Clinical Trials
Why this work is in the frame
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Bibliographic record
Abstract
In recent years, the scientific evidence linking vitamin D status or supplementation to breast cancer has grown notably. To investigate the role of vitamin D supplementation on breast cancer incidence, we conducted a systematic review and meta-analysis of randomized controlled trials comparing vitamin D with placebo or no treatment. We used OVID to search MEDLINE (R), EMBASE and CENTRAL until April 2012. We screened the reference lists of included studies and used the "Related Article" feature in PubMed to identify additional articles. No language restrictions were applied. Two reviewers independently extracted data on methodological quality, participants, intervention, comparison and outcomes. Risk Ratios and 95% Confident Intervals for breast cancer were pooled using a random-effects model. Heterogeneity was assessed using the I(2) test. In sensitivity analysis, we assessed the impact of vitamin D dosage and mode of administration on treatment effects. Only two randomized controlled trials fulfilled the pre-set inclusion criteria. The pooled analysis included 5372 postmenopausal women. Overall, Risk Ratios and 95% Confident Intervals were 1.11 and 0.74-1.68. We found no evidence of heterogeneity. Neither vitamin D dosage nor mode of administration significantly affected breast cancer risk. However, treatment efficacy was somewhat greater when vitamin D was administered at the highest dosage and in combination with calcium (Risk Ratio 0.58, 95% Confident Interval 0.23-1.47 and Risk Ratio 0.93, 95% Confident Interval 0.54-1.60, respectively). In conclusions, vitamin D use seems not to be associated with a reduced risk of breast cancer development in postmenopausal women. However, the available evidence is still limited and inadequate to draw firm conclusions. Study protocol code: FARM8L2B5L.
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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 | 0.025 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.048 | 0.005 |
| 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) | 0.002 | 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 it