Pre-treatment PSA- progression as a negative prognostic factor in patients using 5-alpha-reductase inhibitors prior to radiotherapy for prostate cancer.
Bibliographic record
Abstract
96 Background: To investigate the impact of 5-alpha-reductase inhibitors (5-ARIs) usage on radiotherapy outcomes for localized prostate cancer. Methods: From our institutional database of over 2500 patients, we identified 203 patients on a 5-ARI. They were all treated with either external beam radiotherapy (EBRT) or brachytherapy for localized prostate cancer. Patients receiving a 5-ARI were analyzed according to the following prostate cancer progression criteria: a) progression of Gleason score or increase in cancer volume on the biopsy, b) first biopsy positive for cancer after being treated for urinary symptoms with a 5-ARI, and c) prostate-specific antigen (PSA) progression with or without a previous cancer diagnosis. Biochemical failure (BF) was defined by the Phoenix definition. Log-rank test was used for survival analysis. Results: At a median follow-up of 36 months (interquartile range [IQR] 22-52 months), 10 (4.9%) patients experienced BF. 52% of men demonstrated none of the progression criteria, 37% showed only one prostate cancer progression criteria and 11% showed two. Using a univariate analysis, PSA progression (p = 0.004) and appearance of a positive biopsy (p < 0.001) but not Gleason progression (p = 0.3) were a significant predictive factor of BF. With separate multivariate analysis adjusted for the CAPRA score (HR 1.7, 95% CI 1.2-2.3, p = 0.003), a rising PSA (HR 5.7, 95% CI 1.1-28.8, p = 0.04) and the number of cancer progression factors (HR 2.9, 95%CI 1.2-7.0, p = 0.02) remained adverse risk factors. Both Gleason score progression (p = 0.4) and first biopsy positive for cancer (p = 0.13) failed to remain significant. Age and obesity were not significant factors in univariate or multivariate analysis. Conclusions: A PSA progression experienced while under 5-ARI treatment before EBRT or brachytherapy is predictive of worse biochemical outcome. Such details should be considered when counseling men prior to radiation therapy.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".