Bibliographic record
Abstract
Introduction and Objectives: 5-alpha reductase inhibitors (5ARIs) have been shown to prevent prostate cancer in two large randomized controlled trials.No prior work has shown the effect of 5ARIs on those already diagnosed with low risk prostate cancer.Our goal was to determine the effect of 5ARIs on pathologic progression in men on active surveillance for prostate cancer.Methods: This was a single institution retrospective cohort study comparing men taking a 5ARI versus no 5ARI while on active surveillance for prostate cancer.All men had at least two biopsies.Inclusion criteria for active surveillance were PSA <10 ng/mL, clinical stage T1c/T2a, Gleason score <6, and <3 cores positive with no more than 50% of a core involved at initial diagnostic biopsy.Pathologic progression was evaluated and defined as Gleason score >6, or maximum core involvement >50% or >3 cores positive on a follow-up prostate biopsy.Univariate, multivariate and Kaplan-Meir analyses were conducted.Results: A total of 288 men on active surveillance met the inclusion criteria.The median follow-up was 38.5 months (IQR 23.6-59.4)with 93 men (32%) experiencing pathologic progression and 96 men (33%) abandoning active surveillance.Men taking a 5ARI experienced a lower rate of pathologic progression (18.6% vs 36.7%, p=0.004) and were less likely to abandon active surveillance (20% vs 37.6%, p=0.006).The median time to progression was longer in the 5ARI group (42.5 months) compared to the non-5ARI group (31.5 months; p=0.026).On multivariate analysis, lack of 5ARI use was most strongly associated with pathologic progression (OR 2.98, 95% CI 1.5 -5.9) followed by age and baseline maximum percentage involvement of any biopsy core.Conclusions: 5ARIs were associated with a significantly lower rate of pathologic progression and abandonment of active surveillance.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.373 | 0.173 |
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".