Can active surveillance really reduce the harms of overdiagnosing prostate cancer? A reflection of real life clinical practice in the PRIAS study
Bibliographic record
Abstract
BACKGROUND: Active surveillance (AS) for low-risk prostate cancer (PCa) appears to provide excellent long-term PCa-specific and overall survival. The choice for AS as initial treatment is mainly based on avoiding side effects from invasive treatment; but AS entails regular check-ups and the possibility of still having to switch or deciding to switch to invasive treatment. Here, we assessed the long-term follow-up data from AS in real life clinical practices. METHODS: Data from the first 500 men, enrolled in PRIAS before July 2008 by 30 centers across 8 countries, were analyzed to provide long-term follow-up results. Men were advised to be regularly examined with prostate-specific antigen (PSA) tests, digital rectal examinations, and prostate biopsies. Men were advised to switch to invasive treatment if they had disease reclassification [Gleason score (GS) ≥3+4 on biopsy, more than two positive biopsy cores, a stage higher than cT2] or a PSA-doubling time of 0-3 years. We assessed time on AS, outcomes and reasons for discontinuing AS, and rates of potential unnecessary biopsies and treatments. RESULTS: The median follow-up time was 6.5 years. During this period, 325 (65%) men discontinued after a median of 2.3 years and 121 (24%) men had no recent (>1 year) data-update after a median of 7.3 years. The remaining 54 (11%) men were confirmed to be still on AS. Most men discontinued based on protocol advice; 38% had other reasons. During follow-up, 838 biopsy sessions were performed of which 79% to 90% did not lead to reclassification, depending on the criteria. Of the 325 discontinued men, 112 subsequently underwent radical prostatectomy (RP), 126 underwent radiotherapy, 57 switched to watchful waiting (WW) or died, and 30 had another or unknown treatment. RP results were available of 99 men: 34% to 68%, depending on definition, had favorable outcomes; 50% of unfavorable the outcomes occurred in the first 2 years. Of the 30 (6%) men who died, 1 man died due to PCa. CONCLUSIONS: These data, reflecting real life clinical practice, show that more than half of men switched to invasive treatment within 2.3 years, indicating limitations to the extent in which AS is able to reduce the adverse effects of overdiagnosis. Therefore, despite guidelines stating that PCa diagnosis must be uncoupled from treatment, it remains important to avoid overdiagnosing PCa as much as possible.
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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 | 0.027 | 0.068 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".