Predictors of time to biochemical recurrence in a radical prostatectomy cohort within the PSA-era
Bibliographic record
Abstract
INTRODUCTION: We sought to determine predictors for early and late biochemical recurrence following radical prostatectomy among localized prostate cancer patients. METHODS: The study included localized prostate cancer patients treated with radical prostatectomy (RP) at the University of Southern California from 1988 to 2008. Competing risks regression models were used to determine risk factors associated with earlier or late biochemical recurrence, defined using the median time to biochemical recurrence in this population (2.9 years after radical prostatectomy). RESULTS: The cohort for this study included 2262 localized prostate cancer (pT2-3N0M0) patients who did not receive neoadjuvant or adjuvant therapies. Of these patients, 188 experienced biochemical recurrence and a subset continued to clinical recurrence, either within (n=19, 10%) or following (n=13, 7%) 2.9 years after RP. Multivariable stepwise competing risks analysis showed Gleason score ≥7, positive surgical margin status, and ≥pT3a stage to be associated with biochemical recurrence within 2.9 years following surgery. Predictors of biochemical recurrence after 2.9 years were Gleason score 7 (4+3), preoperative prostate-specific antigen (PSA) level, and ≥pT3a stage. CONCLUSIONS: Higher stage was associated with biochemical recurrence at any time following radical prostatectomy. Particular attention may need to be made to patients with stage ≥pT3a, higher preoperative PSA, and Gleason 7 prostate cancer with primary high-grade patterns when considering longer followup after RP.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".