Concordance between transrectal ultrasound guided biopsy results and radical prostatectomy final pathology: Are we getting better at predicting final pathology?
Bibliographic record
Abstract
INTRODUCTION: Inaccuracy in biopsy Gleason scoring poses a risk to men who may then receive inappropriate treatment. We assess whether there was a change in discordance rates between biopsy and radical prostatectomy at our institution in recent years, while considering the implementation of active surveillance and the shift in biopsy scores caused by the 2005 International Society of Urologic Pathology update to the Gleason scoring protocol. METHODS: We reviewed patients who underwent radical prostatectomy at our institution between May 2004 and April 2011. We analyzed clinical and pathological correlates of upgrading in 3 subgroups: Gleason sum (GS) 6/6, GS6/7 and GS7/7, where the sum preceding the dash was determined from biopsy and the subsequent sum was determined from the radical prostatectomy specimen. We applied the log-rank test and Cox model to a Kaplan Meier analysis of biochemical recurrence in the subgroups, and also mapped GS6/7 discordance over time. RESULTS: In total, 1717 patients met our inclusion criteria. The 3 subgroups had significantly different mean prostate-specific antigen, patient age, tumour volume, margin status, pathologic stage, prostate weight, transrectal ultrasound volume and rate of progression (p < 0.05). We noted a multiphasic trend with a fall in discordance after 2005. However, there was no sustained trend over the study period taken as a whole (p = 0.06). CONCLUSIONS: Although no sustained trend was observed, the falling discordance after 2005 may reflect the accommodation to the Gleason scoring update, while the gradual adoption of active surveillance may have led to the otherwise increasing trends. However, our observations may also be spurious biopsy sampling errors.
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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 | 0.011 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".