Prevalence and Predictors of Selenium and Vitamin E Supplementation in a Urology Population
Bibliographic record
Abstract
OBJECTIVES: Preclinical and epidemiological studies have suggested the use of supplements such as selenium and vitamin E for prostate cancer (PCa) prevention; however, clinical trials have not demonstrated clear benefit in patients. This study aims to investigate the current prevalence and predictors for use of these supplements in men in a urology population. DESIGN, SUBJECTS, AND OUTCOMES MEASURED: Three hundred and twelve (312) men visiting the Princess Margaret Hospital Ambulatory Urology Clinic were enrolled in this University Health Network Research Ethics Board-approved questionnaire-based study investigating supplement use, reasons for use and demographic characteristics. RESULTS: It was observed that 13.5% and 20.8% of the participants are currently using selenium and vitamin E, respectively, while 10.6% and 15.7% previously used selenium and vitamin E, respectively. Both education (percentage of users comparing less than college education versus college or above education: selenium: 14% versus 28%; p=0.008, vitamin E: 26% versus 41%; p=0.013) and health literacy (mean scores±standard error of the mean of users versus nonusers: selenium question 1: 1.4507±0.09576 versus 1.6083±0.07211; p=0.023, selenium question 2: 2.8750±0.04395 versus 2.7106±0.03774; p=0.000, selenium question 3: 1.4583±0.08377 versus 1.7064±0.06278; p=0.025, vitamin E question 1: 2.8036±0.04545 versus 2.7179±0.04097; p=0.010, vitamin E question 2: 1.5446±0.06698 versus 1.7077±0.07241; p=0.006) are predictors of selenium and vitamin E use on univariable analysis. On multivariable analysis education (selenium odds ratio=2.095, 95% confidence interval=1.019-4.305, p=0.044; vitamin E odds ratio=1.855, 95% confidence interval=1.015-3.338, p=0.045) remains a significant predictor of selenium and vitamin E use. Examining the data on use by education, it was found that more men with a higher education attributed their use of selenium to urologist advice (24%), and those with a lower education attributed their use of selenium to naturopath/homeopath advice (28%). CONCLUSIONS: Many men who visit urology clinics use selenium and vitamin E despite the lack of clinical support for chemoprevention. Education and health literacy are important variables in determining the use of these supplements in these men. This information may aid in addressing the needs of the diverse patient population using these supplements for the prevention of PCa.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".