Randomized Clinical Trial of Vitamin D3 Doses on Prostatic Vitamin D Metabolite Levels and Ki67 Labeling in Prostate Cancer Patients
Bibliographic record
Abstract
CONTEXT: Vitamin D3 might benefit prostate cancer (PCa) patients because prostate cells can locally synthesize the active hormone calcitriol. OBJECTIVE: Our objective was to determine the effects of oral vitamin D3 on vitamin D metabolites and PCa proliferative activity in prostate tissue. DESIGN AND SETTING: We conducted a double-blind randomized clinical trial at surgical oncology clinics in Toronto, Canada. PATIENTS: PCa patients (Gleason 6 or 7) participated in the study. Of 66 subjects who were enrolled, 63 completed the dosing protocol. INTERVENTION: Vitamin D3 (400, 10 000, or 40 000 IU/d) was orally administered before radical prostatectomy. MAIN OUTCOME MEASURES: We evaluated vitamin D metabolite levels and Ki67 labeling in surgical prostate tissue. Safety measures, PTH, and prostate-specific antigen (PSA) were also assessed. RESULTS: Prostate tissue and serum levels of vitamin D metabolites, including calcitriol, increased dose dependently (P < .03) and were significantly higher in the 40 000-IU/d group than in every other dose group (P < .03). Prostate vitamin D metabolites correlated positively with serum levels (P < .0001). Ki67 measures did not differ significantly among vitamin D dose groups. However, cross-sectional analysis indicated that the calcitriol level attained in prostate was inversely associated with Ki67 intensity and Ki67 (3+) percent positive nuclei in PCa and benign tissue (P < .05). Safety measures did not change adversely with dosing. Compared with the 400-IU/d group, serum PTH and PSA were lower in the combined higher-dose groups at the end of the study (P < .02). CONCLUSIONS: Oral vitamin D3 raised prostate calcitriol levels (level 1 evidence) and modestly lowered both PSA and PTH. Although Ki67 expression did not differ among dose groups, its levels correlated inversely with prostate calcitriol. These suggestions of clinical benefit justify continued clinical research.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".