Vitamin D in the Breast Cancer Continuum: A Systematic Review and Meta-Analysis of Primary Prevention, Patient Prognosis, and Adjunctive Treatment Response
Bibliographic record
Abstract
Background: The role of vitamin D across the breast cancer spectrum remains complex and contested. Compelling preclinical antineoplastic mechanisms contrast with inconsistent clinical findings. Large randomized controlled trials (RCTs) show null effects for primary prevention, while observational studies often link higher vitamin D status at diagnosis with better prognosis. Key conflicts include this prevention-prognosis disconnect, debates over linear versus J-shaped prognostic dose-responses, and a "receptor-status paradox" where estrogen receptor-positive (ER-positive) disease shows prognostic links, but hormone receptor-negative (HR-negative)/triple-negative (TNBC) subtypes derive greater benefit (improved pathological complete response, pCR) from vitamin D intervention during neoadjuvant chemotherapy (NACT). This study systematically synthesizes evidence across these distinct clinical contexts. Methods: Following PRISMA guidelines, we systematically reviewed PubMed, EMBASE, and CENTRAL (January 1st, 2014–September 2nd, 2025) for high-impact RCTs and large prospective cohort studies evaluating vitamin D supplementation or serum 25-hydroxyvitamin D (25(OH)D) levels regarding breast cancer incidence, prognosis (survival/recurrence), or pCR after NACT. Quality was assessed (Cochrane RoB 2; Newcastle-Ottawa Scale). Data were extracted dually. Findings were synthesized stratigraphically (prevention, prognosis, treatment). A random-effects meta-analysis pooled pCR data from NACT RCTs. Results: Six high-quality studies (3 RCTs, 3 cohorts; N=31,026) were included. (1) Prevention: The VITAL RCT (N=25,871; mean baseline 25(OH)D 30.8 ng/mL) found no reduction in incident invasive breast cancer with 2000 IU/day vitamin D3 (HR 1.02, 95% CI 0.79–1.31). (2) Prognosis: Cohort studies (N=4,835) showed higher 25(OH)D linked to better OS (Adj HR T3 vs T1: 0.72). Complexity emerged: one study linked benefit specifically to ER-positive recurrence (Adj HR 0.87), while another reported a J-shaped curve for EFS, with worse outcomes at both low (≤52 nmol/L; Adj HR 1.63) and high (≥99 nmol/L; Adj HR 1.37) levels versus intermediate. (3) Treatment: Meta-analysis of two NACT RCTs (N=310) showed vitamin D supplementation significantly increased pCR rates (38.1% vs 22.6%; Pooled RR 1.69, 95% CI 1.21–2.36; P=0.002; I²=0%). Subgroup data strongly suggested greater benefit in HR-negative/TNBC and baseline-deficient patients. Conclusion: Vitamin D supplementation appears ineffective for primary breast cancer prevention in replete populations. Its prognostic role is complex, suggesting an optimal 25(OH)D range (potentially ~30-40 ng/mL) and possible ER-specific hormonal modulation effects, though causality from observational data remains uncertain. Critically, vitamin D intervention during NACT significantly improves pCR, particularly in HR-negative/TNBC, likely via distinct chemosensitization/immunomodulatory mechanisms. This synthesis provides a framework for understanding these context-dependent roles, supporting vitamin D assessment and potentially adjunctive NACT supplementation, especially in deficient patients with aggressive subtypes, pending necessary validation in larger trials.
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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 | 0.019 | 0.051 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.028 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".