The relationship between serum vitamin D levels and breast cancer prognosis: A meta-analysis.
Bibliographic record
Abstract
1521 Background: Vitamin D (VitD) is a circulating hormone known to regulate gene transcription in breast cancer (BC) cells. The association between VitD and BC risk has been extensively studied. Until recently, however, the role of VitD in BC progression and its association with clinical outcomes among BC patients was poorly understood. To assess these new developments, a systematic review and meta-analysis was performed. Methods: A systematic review and meta-analysis by searching MEDLINE (1982 – 2012), ASCO, and SABCS for abstracts (2009 – 2012), with the following keywords: “breast cancer” and “prognosis” or “survival”, and “vitamin D” or ”calcitriol.” Abstracts were scrutinized for reports correlating serum VitD levels with breast cancer clinical outcomes, including: disease-free survival (DFS) and overall survival (OS). Studies were included if serum VitD samples were taken shortly after diagnosis and survival data were reported. Meta-analyses were performed using an inverse-variance weighted fixed-effects model. Results: We identified 7 studies reporting correlative data between serum VitD levels and BC survival. These data included 4,885 patients evaluated for DFS and 3858 patients evaluated for OS. VitD-deficiency was defined as <30ng/mL, <20ng/mL, and <14ng/mL in 3, 3, and 1 studies, respectively, and was identified in an average of 48.1% of patients (range: 17.9-87.8%). VitD deficiency was associated with a pooled hazard ratio (HR) of 2.13 (CI: 1.64 - 2.78) and 1.76 (CI: 1.35 - 2.30) for DFS and OS, respectively. Conclusions: To our knowledge, this is the first report of a meta-analysis of the relationship between serum VitD and BC prognosis. The prevalence of VitD-deficiency varied widely across studies and may reflect differences in geographic location, race, and rates of supplementation across patient populations. These findings support the hypothesis that VitD-deficient breast cancer patients have poorer clinical outcomes than VitD sufficient patients; but do not establish whether this relationship is causative. Further studies are warranted to investigate the possible protective effects of VitD supplementation on survival among VitD-deficient BC patients.
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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 | 0.010 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.048 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".