Sleep quality and prostate cancer aggressiveness: Results from the REDUCE trial
Bibliographic record
Abstract
BACKGROUND: Disrupted sleep has been associated with increased risk of certain cancers. Little data exist in prostate cancer. We tested the association between sleep quality and prostate cancer diagnosis overall and by tumor grade in the Reduction by Dutasteride of Prostate Cancer Events chemoprevention trial. We hypothesized that worse sleep quality would be associated with increased tumor aggressiveness. METHODS: At baseline, 5614 men completed a validated six-item questionnaire on sleep quality. We generated a composite score categorized into tertiles to measure overall sleep quality and assessed each sleep quality question individually. Logistic regression was used to test associations between baseline sleep quality and overall, low-grade and high-grade prostate cancer diagnosis at 2-year study-mandated biopsy. Models were stratified by nocturia. RESULTS: 1.39; 95% CI: 1.01-1.92). Men reporting trouble falling asleep at night sometimes vs never had elevated odds of high-grade prostate cancer (OR: 1.51; 95% CI: 1.08-2.09) while trouble staying awake during the day was associated with decreased odds of low-grade prostate cancer (OR: 0.65; 95% CI: 0.49-0.86). Results were similar within strata of nocturia severity. CONCLUSIONS: Overall, associations between sleep quality and prostate cancer were inconsistent. However, there was some evidence for a positive association between insomnia and high-grade prostate cancer, and an inverse relationship between daytime sleepiness and low-grade prostate cancer; findings that should be validated by future studies.
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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".