Presence of biopsy Gleason pattern 5 + 3 is associated with higher mortality after radical prostatectomy but not after external beam radiotherapy compared to other Gleason Grade Group IV patterns+
Bibliographic record
Abstract
BACKGROUND: We hypothesized that Gleason Grade Group (GGG) IV patients treated with radical prostatectomy (RP) or external beam radiotherapy (EBRT) exhibit different cancer-specific mortality (CSM) rates according to underlying Gleason patterns (GP): 4 + 4 versus 3 + 5 versus 5 + 3. MATERIALS AND METHODS: We identified all GGG IV patients treated with either RP or EBRT within the Surveillance, Epidemiology, and End Results 2004-2016 database. The effect of biopsy GP on CSM (3 + 5 vs. 4 + 4 vs. 5 + 3) was tested in Kaplan-Meier and multivariable competing risks regression models (adjusted for PSA, age at diagnosis, cT-, and cN-stage). RESULTS: Of 26,458 GGG IV patients, 14,203 (53.7%) were treated with EBRT and 12,255 (46.3%) with RP. Of RP patients, 15.3 versus 81.2 versus 3.4% exhibited biopsy GP 3 + 5 versus 4 + 4 versus 5 + 3 and respective 10-year CSM rates were 6.5 versus 6.2 versus 12.6% (p < .001). In multivariable analyses addressing RP patients, GP 5 + 3 was associated with two-fold higher CSM rate than GP 4 + 4 (p < .001), but not GP 3 + 5 (p = .1). Of EBRT patients, 7.6 versus 89.8 versus 2.6% exhibited biopsy GP 3 + 5 versus 4 + 4 versus 5 + 3 and respective 10-year CSM rates were 12.2 versus 13.8 versus 17.8% (p < .001). In multivariable analyses addressing EBRT patients, no CSM differences according to GP were observed (all p ≥ .4). CONCLUSION: In GGG IV RP candidates, the presence of biopsy GP 5 + 3 purports a significantly higher CSM than in GP 4 + 4 or 3 + 5. In GGG IV EBRT candidates, no significant CSM differences according to GP were recorded.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.002 | 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".