Five-year follow-up of active surveillance for prostate cancer: A Canadian community-based urological experience
Bibliographic record
Abstract
INTRODUCTON: We assessed oncological outcomes of active surveillance (AS) using a community database and identified factors associated with disease reclassification on surveillance biopsy. METHODS: A retrospective review was performed on 200 men on AS. Prostate-specific antigen (PSA) was measured every 3 to 6 months. Prostate biopsies were performed every 1 to 4 years, and at the individual physician's discretion. Disease reclassification was defined as clinical T1 to cT2 progression, or histologically as >2 cores positive, Gleason score >6, or >50% core involvement on surveillance biopsy. Multivariate Cox regression analysis evaluated factors associated with disease reclassification. Kaplan-Meier survival curves were plotted. RESULTS: We assessed a heterogeneous cohort of 86 patients, with a median age 67.2 years, who received ≥1 surveillance biopsies. The median follow-up was 5.2 years. The median times to first and second surveillance biopsies were 730 and 763 days, respectively. Overall, 47% of patients were reclassified on surveillance biopsy after a median 2.1 years. Factors associated with disease reclassification were PSA density >0.20 (p < 0.0001, hazard ratio [HR] 4.55, 95% confidence interval [CI] 2.116-9.782) and ≥3 positive cores (p = 0.0152, HR 3.956, 95% CI 1.304-12.003) at diagnosis, and number of positive cores on surveillance biopsy. In total, 25 (29%) patients received delayed intervention, with a median time to intervention of 2.6 years. The median time on AS was 4.4 years, with an overall survival of 95% and prostate-specific survival of 100%. CONCLUSIONS: Our community study supports AS to reduce over-treatment of prostate cancer. PSA density >0.20 and ≥3 cores positive are associated with disease reclassification on surveillance biopsy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".