Got central prostate pathology review? A cross-sectional audit of 2009 versus 2003 outcomes.
Bibliographic record
Abstract
196 Background: Prostate cancer is the most common non-cutaneous cancer in Canadian men; over 24,000 will be newly diagnosed and 4,300 will die from it in 2010. Estimating an individual's risk of disease spreading across the capsule and probability of recurrence with different treatment modalities is common practice in prostate cancer management and often drive the choice or extent of treatment options. A strong predictor of recurrence and organ confined disease is tumor grade. The literature recognizes differences in grading prostate cancer between genitourinary and non-specialized pathologists; we previously reported a 30% change in risk category (Low, GS 2-6; Int., GS 7; High, GS 8-10). However, this report was based on data from 2003/2004. A repeat audit was necessary given Gleason grading practice changes following the 2005 ISUP Consensus Conference. Methods: Log books from 2009/10 where our Genitourinary Pathologists (GUP) reviewed prostate needle core biopsies were used to identify cases; a retrospective chart review was completed. The following variables were extracted: 1° Gleason score; 2° Gleason score; number of sites; % Gleason 4/5 pattern (overall); perineural invasion (present/absent); extracapsular extension (present/absent). Descriptive statistics were used to summarize the results. Results: The charts of 132 patients having a GUP biopsy review were extracted. Seventeen percent (22/132) of cases changed risk category. Of the 47 low risk cases, 23% (11/47) were up-graded in risk category (21% by 1 category; 2% by 2 categories). Of the 46 intermediate risk cases, 15% (7/46) were up-graded and 2% (1/46) were down-graded. Of the 39 high risk cases, only 8% (3/39) were down-graded by 1 risk category. Comparatively, there was a 43% reduction in risk category change between 2003/04 (30%) and 2009/10 (17%). Conclusions: Despite this reduction, a clinically significant proportion of patients changed pathologic risk category upon GUP review. Thus, it is recommended that prostate cancer pathology be routinely reviewed by a GUP as a best practice to optimize management and quality of care. Strategies are still needed to address disparities in pathologic grading and represent a potential area for further investigation. No significant financial relationships to disclose.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 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 | 0.001 |
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".