Prognostic Effects of 25-Hydroxyvitamin D Levels in Early Breast Cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: Vitamin D has been linked to breast cancer risk, but prognostic effects are unknown. Such effects are biologically plausible given the presence of vitamin D receptors in breast cancer cells, which act as nuclear transcription factors to regulate gene activity. PATIENTS AND METHODS: The study was conducted in a prospective inception cohort of 512 women with early breast cancer diagnosed 1989 to 1996. Vitamin D levels were measured in stored blood. Clinical, pathologic, and dietary data were accessed to examine prognostic effects of vitamin D. RESULTS: Mean age was 50.4 years, mean vitamin D was 58.1 +/- 23.4 nmol/L. Vitamin D levels were deficient (< 50 nmol/L) in 37.5% of patients, insufficient (50 to 72 nmol/L) in 38.5% of patients, and sufficient (> 72 nmol/L) in 24.0% of patients. There was little variation in mean vitamin D levels between summer and winter months. Mean follow-up was 11.6 years; 116 women had distant recurrences, and 106 women died. Women with deficient vitamin D levels had an increased risk of distant recurrence (hazard ratio [HR] = 1.94; 95% CI, 1.16 to 3.25) and death (HR = 1.73; 95% CI, 1.05 to 2.86) compared with those with sufficient levels. The association remained after individual adjustment for key tumor and treatment related factors but was attenuated in multivariate analyses (HR = 1.71; 95% CI, 1.02 to 2.86 for distant recurrence; HR = 1.60; 95% CI, 0.96 to 2.64 for death). CONCLUSION: Vitamin D deficiency may be associated with poor outcomes in breast cancer.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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