Utility of 5-alpha-reductase inhibitors in active surveillance for favourable risk prostate cancer
Bibliographic record
Abstract
INTRODUCTION: This retrospective review compares prostate-specific antigen (PSA) doubling time (DT) prior to the initiation of a 5-alpha-reductase inhibitor (pre-5-ARI) to after the PSA nadir (post-nadir) has been reached for patients on active surveillance for favourable-risk prostate cancer. METHODS: Between 1996 and 2010, a total of 100 men with a history of 5-ARI use were captured from our active surveillance database. Twenty-nine patients had a sufficient number of PSA values to determine both pre-5-ARI and post-nadir DTs. PSADT was calculated using the general linear mixed-model method. RESULTS: The median follow-up was 69.5 months. The median pre-5-ARI PSADT was 55.8 (range: 6-556.8) months, while the post-nadir value was 25.2 (range: 6-231) months (p = 0.0081). Six patients were reclassified after an average of 67.7 (range: 59-95) months, due to progression in PSADT (n = 2) or Gleason score (n = 4). The median pre-5-ARI and post-nadir DTs for this group were 42.3 (range: 32.4-91.1) and 21.1 (range: 6-44.3) months, respectively. CONCLUSION: 5-ARIs significantly decreased PSADT compared to prior to their initiation. This effect may be due to preferential suppression of benign tissue following PSA nadir. The resulting PSADT would then represent a more accurate depiction of the true cancer-related DT. If validated with a larger cohort, 5-ARIs may enhance the utility of PSADT as a biomarker of disease progression in 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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".