Positive surgical margins at radical prostatectomy: Population-based averages within PSA and Gleason strata
Bibliographic record
Abstract
BACKGROUND: Positive surgical margins (PSM) are an important determinant of biochemical recurrence after radical prostatectomy (RP). We use a population-based cancer registry to evaluate PSM by stage, Gleason and prostate-specific antigen (PSA). METHODS: We identified men undergoing RP from the Surveillance, Epidemiology and End Results (SEER) database between 2004 and 2007. Differences between those with and without PSM were compared with chi-squared tests. The proportion of cases with PSM were stratified by PSA and Gleason sum for both pT2 and pT3a tumours. Factors associated with PSM were analyzed using chi square and multivariate logistic regression analysis. A composite variable was used in a second multivariate analysis to display the odds ratio (OR) for a PSM for each discrete combination of PSA, Gleason score and pT stage. RESULTS: In total, 28 461 RP patients were identified and a PSM was present in 19.5%. PSM were 42% in pT3a and 16% in pT2 cases. Higher PSAs (<4.0, 4-9.9, >10) were associated with higher proportions of PSM (12%, 20% and 28%, p < 0.001). Similarly, higher Gleason scores (≤6, 3+4, 4+3, ≥8) were associated with higher PSM (12%, 22%, 27% and 33%, p < 0.001). For pT2 tumours, the proportion of PSM ranged from 8% (Gleason ≤6, PSA <4.0) to 28% (Gleason 8-10, PSA ≥10). For pT3a tumours, the PSM was higher in each Gleason/PSA strata compared to those with pT2 tumours, reaching 63% for those with pT3a, Gleason 8-10, PSA >10 disease. On multivariate analysis, stage was the largest predictor for PSM (OR 3.05, 95% confidence interval 2.81-3.30), although Gleason score and PSA remained statistically significant. CONCLUSION: In this population-based study of PSM after RP, the proportion of PSM vary significantly within different PSA and Gleason strata for organ-confined and extracapsular disease. These data can be used as a reference for urologist self-assessment.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".