Long-Term Follow-Up of a Large Active Surveillance Cohort of Patients With Prostate Cancer
Bibliographic record
Abstract
PURPOSE: Active surveillance is increasingly accepted as a treatment option for favorable-risk prostate cancer. Long-term follow-up has been lacking. In this study, we report the long-term outcome of a large active surveillance protocol in men with favorable-risk prostate cancer. PATIENTS AND METHODS: In a prospective single-arm cohort study carried out at a single academic health sciences center, 993 men with favorable- or intermediate-risk prostate cancer were managed with an initial expectant approach. Intervention was offered for a prostate-specific antigen (PSA) doubling time of less than 3 years, Gleason score progression, or unequivocal clinical progression. Main outcome measures were overall and disease-specific survival, rate of treatment, and PSA failure rate in the treated patients. RESULTS: Among the 819 survivors, the median follow-up time from the first biopsy is 6.4 years (range, 0.2 to 19.8 years). One hundred forty-nine (15%) of 993 patients died, and 844 patients are alive (censored rate, 85.0%). There were 15 deaths (1.5%) from prostate cancer. The 10- and 15-year actuarial cause-specific survival rates were 98.1% and 94.3%, respectively. An additional 13 patients (1.3%) developed metastatic disease and are alive with confirmed metastases (n = 9) or have died of other causes (n = 4). At 5, 10, and 15 years, 75.7%, 63.5%, and 55.0% of patients remained untreated and on surveillance. The cumulative hazard ratio for nonprostate-to-prostate cancer mortality was 9.2:1. CONCLUSION: Active surveillance for favorable-risk prostate cancer is feasible and seems safe in the 15-year time frame. In our cohort, 2.8% of patients have developed metastatic disease, and 1.5% have died of prostate cancer. This mortality rate is consistent with expected mortality in favorable-risk patients managed with initial definitive intervention.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".