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Record W4415718011 · doi:10.37275/bsm.v10i1.1486

Vitamin D in the Breast Cancer Continuum: A Systematic Review and Meta-Analysis of Primary Prevention, Patient Prognosis, and Adjunctive Treatment Response

2025· review· W4415718011 on OpenAlexaboutno aff
Felix Setiawan, Yan Wisnu Prajoko, Niken Puruhita, Aliva Nabila Farinisa

Bibliographic record

VenueBioscientia Medicina Journal of Biomedicine and Translational Research · 2025
Typereview
Language
FieldMedicine
TopicVitamin D Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBreast cancerRandomized controlled trialVitamin D and neurologyCohortObservational studyChemotherapyPathologicalCancerCohort study

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.030
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.551
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0300.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0100.001
Bibliometrics0.0070.009
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.122
GPT teacher head0.444
Teacher spread0.322 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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