Risk of Prostate Cancer in a Randomized Clinical Trial of Calcium Supplementation
Bibliographic record
Abstract
BACKGROUND: In some studies, high calcium intake has been associated with an increased risk of prostate cancer, but no randomized studies have investigated this issue. METHODS: We randomly assigned 672 men to receive either 3 g of calcium carbonate (1,200 mg of calcium), or placebo, daily for 4 years in a colorectal adenoma chemoprevention trial. Participants were followed for up to 12 years and asked periodically to report new cancer diagnoses. Subject reports were verified by medical record review. Serum samples, collected at randomization and after 4 years, were analyzed for 1,25-(OH)2 vitamin D, 25-(OH) vitamin D, and prostate-specific antigen (PSA). We used life table and Cox proportional hazard models to compute rate ratios for prostate cancer incidence and generalized linear models to assess the relative risk of increases in PSA levels. RESULTS: After a mean follow-up of 10.3 years, there were 33 prostate cancer cases in the calcium-treated group and 37 in the placebo-treated group [unadjusted rate ratio, 0.83; 95% confidence interval (95% CI), 0.52-1.32]. Most cases were not advanced; the mean Gleason's score was 6.2. During the first 6 years (until 2 years post-treatment), there were significantly fewer cases in the calcium group (unadjusted rate ratio, 0.52; 95% CI, 0.28-0.98). The calcium risk ratio for conversion to PSA >4.0 ng/mL was 0.63 (95% CI, 0.33-1.21). Baseline dietary calcium intake, plasma 1,25-(OH)2 vitamin D and 25-(OH) vitamin D levels were not materially associated with risk. CONCLUSION: In this randomized controlled clinical trial, there was no increase in prostate cancer risk associated with calcium supplementation and some suggestion of a protective effect.
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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 | 0.013 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".