Bibliographic record
Abstract
Introduction: Active surveillance (AS) is widely accepted as a treatment pathway for low-risk and favorable intermediate-risk localized prostate cancer.We aimed to report the long-term progression of patients on AS to treatment.Methods: In a retrospective cohort study performed at a single institution center, 2521 men with low or favorable intermediate-risk prostate cancer were managed with an active surveillance protocol from 2000-2023.Main outcomes measured were overall survival and time to treatment.Results: Of the patients enrolled, 620 (24.6%) entered treatment, 395 (15.7%) patients died, 34 (1.3%) had metastasis, and six (17.6% of those with metastasis) died with metastasis.By race, 2337 (92.7%) were White, 143 (5.7%) African-American, 20 (0.8%) American Indian/Alaskan, 14 (0.6%) Asian, and seven (0.2%) other.Median followup was four years and maximum followup time was 22.2 years.Median age of patients was 73.8 with a range of 43.8 to 98.1 years.At five, 10, and 15 years, 71.3%, 62.7%, and 52% of patients remained untreated and on AS.For patients with Gleason score (GS) 3+3=6 on AS at five and 10 years, 81.4% and 76.3% remained untreated.Similarly, patients with GS 3+4=7 demonstrated 41.5% and 27.4% untreated rates.Conclusions: To our knowledge, we report the largest AS cohort examining time to treatment.AS for favorable-risk prostate cancer seems safe and effective in the 10-year timespan.In our study, 24.6% of patients progressed to treatment and 1.3% of patient developed metastasis.Additionally, 0.2% of patients on AS died with metastasis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.233 | 0.148 |
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".