Characteristics and outcome of prostate cancer patients with overall biopsy Gleason score 3 + 4 = 7 and highest Gleason score 3 + 4 = 7 or > 3 + 4 = 7
Bibliographic record
Abstract
AIM: Prostate cancer heterogeneity and multifocality might result in different Gleason scores (GS) at individual biopsy cores. According to World Health Organisation/International Society of Urologic Pathology (WHO/ISUP) guidelines, the GS in each biopsy core should be recorded with optional reporting of overall GS for the entire case. We aimed to compare the clinicopathological characteristics and outcome of men with overall biopsy GS 3 + 4 = 7 with highest GS 3 + 4 = 7 (HI = OV) to those with highest GS > 3 + 4 = 7 (HI > OV). METHODS AND RESULTS: Prostate cancer biopsies from the European Randomised Study of Screening for Prostate Cancer (ERSPC) were revised according to WHO/ISUP 2014 guidelines (n = 1031). In total, 370 patients had overall GS 3 + 4 = 7, 60 of whom (16%) had had at least one biopsy core with GS 4 + 3 = 7 or 4 + 4 = 8. Men with higher GS than 3 + 4 (HI > OV) in any of the cores had higher age, prostate-specific antigen (PSA) level, number of positive biopsies, percentage tumour involvement, percentage Gleason grade 4 and cribriform or intraductal growth (all P < 0.05) than those with GS 3 + 4 = 7 at highest (HI = OV). In multivariable Cox regression analysis, including PSA, percentage positive biopsies and percentage tumour involvement, biochemical recurrence-free survival after radical prostatectomy (P = 0.52) or radiotherapy (P = 0.35) was not statistically different between both groups. CONCLUSION: Among patients with overall GS 3 + 4 = 7, those with highest GS > 3 + 4 = 7 had worse clinicopathological features, but clinical outcome was not statistically significant. Therefore, the use of overall GS instead of highest GS for clinical decision-making is justified, potentially preventing overtreatment in prostate cancer patients.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".