Influence of Regular Statin Intake on Prostate‐Specific Antigen Values, Prostate Cancer Incidence and Overall Survival in a Prospective Screening Trial ( <scp>ERSPC</scp> Aarau)
Bibliographic record
Abstract
OBJECTIVE: While statins have demonstrated a variety of antineoplastic effects in preclinical studies, several retrospective clinical studies and observational studies have not shown a consistent chemopreventive benefit against prostate cancer (PCa). Therefore, in this population-based cohort study, we examined the association of statin intake on prostate specific antigen (PSA) values and risk of development of PCa. METHOD: N = 4,314 men from the Swiss section of the European Randomized Study of Screening for Prostate Cancer (ERSPC) were evaluated. N = 761 men were statin users [Stat+]. The median follow-up was 9.6 years. A transrectal prostate biopsy was performed in men with a PSA-level ≥ 3 ng/mL. Mortality and incidence data was obtained through registry linkages. PCa incidence, total serum PSA level, free-to-total PSA level, and overall survival were compared between [Stat+] and [Stat-] patients. RESULTS: Total PSA values were significantly lower in [Stat+] patients at baseline (1.5 vs. 1.8 ng/mL, p < 0.001) and at last follow-up (1.8 vs. 2.1 ng/mL, p < 0.001). PCa detection during the follow-up period was significantly associated with baseline PSA. The overall incidence of PCa showed no statistical difference among [Stat+] and [Stat-] groups (7.4% vs. 9.5%, p = 0.08), indicating that statin use had no effect on the risk of developing PCa during follow-up. [Stat+] patients had a significantly higher overall mortality risk compared to [Stat-] patients (HR 2.04, p < 0.001). DISCUSSION: A significant risk reduction in the development of PCa in [Stat+] patients was not found. We did observe lower PSA values among [Stat+] patients, compared to [Stat-] patients, with an increasing difference during follow-up.
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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) | 0.001 | 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".