Long‐term cancer control outcomes in patients with biochemical recurrence and the impact of time from radical prostatectomy to biochemical recurrence
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Rates of metastatic progression (MP) and prostate cancer mortality (PCSM) are variable after biochemical recurrence (BCR) in patients who underwent radical prostatectomy (RP). To describe long-term oncological outcomes of BCR patients and to analyze risk factors for further outcomes in these men with a special focus on RP-BCR time. METHODS: We retrospectively analyzed the data of 5509 RP patients treated between 1992 and 2006. Of those, we included 1321 patients who experienced BCR (PSA level ≥0.2 ng/mL) and did not receive any neoadjuvant or adjuvant therapy. Kaplan-Meier and time dependent Cox regression models were used. RESULTS: Median follow-up was 121 months. MP was recorded in 177 (13.4%), PCSM in 126 (9.5%), and overall mortality (OM) in 264 (20.0%) patients. Patients with MP had worse tumor characteristics such as higher Gleason Scores (GS), rapid PSA doubling-time (DT), and shorter RP-BCR time intervals. MP-free, PCSM-free, and overall survival rates were significantly worse in patients with RP-BCR time of <12 months versus patients with 12-35.9 or ≥36 months (P ≤ 0.001). Besides higher GS and rapid PSA-DT, RP-BCR time independently predicted MP, PCSM, and OM in multivariable regression analyses. Relative to the intermediate and longest RP-BCR time interval, the shortest interval (<12) carried the highest risk for all three endpoints. CONCLUSIONS: Only a small proportion of BCR patients proceed to MP or PCSM. Besides higher GS and rapid PSA-DT a shorter RP-BCR interval (<12 months) heralds the most aggressive phenotype for progression to all three examined endpoints: MP, PCSM, and OM.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it