Prostatic ductal adenocarcinoma: An aggressive variant that is underdiagnosed and undersampled on transrectal ultrasound (TRUS)-guided needle biopsy
Bibliographic record
Abstract
INTRODUCTION: We sought to determine if prostatic ductal adenocarcinoma is undersampled and/or underdiagnosed at transrectal ultrasound (TRUS)-guided biopsy. METHODS: With institutional review board approval, we searched our pathology database between 2008 and 2014 for patients with a diagnosis of ≥10% ductal adenocarcinoma on radical prostatectomy and available TRUS-guided needle biopsy specimens. Three blinded genitourinary pathologists independently examined the biopsy slides. The presence or absence of ductal adenocarcinoma was determined. Diagnostic accuracy was calculated using consensus diagnosis as the reference standard. Inter-observer agreement was assessed using Cohen's kappa coefficient. RESULTS: Based on consensus review, 66.7% (12/18) biopsy specimens demonstrated ductal adenocarcinoma and 33.3% (6/18) demonstrated conventional acinar prostatic adenocarcinoma. The sensitivity/specificity for each reader (R) was: 83/100% (R1), 100/83% (R2) and 58/83% (R3) and the inter-observer agreement was only fair (K=0.32). Only two of the original needle-biopsy reports correctly identified ductal adenocarcinoma (sensitivity = 17%). The main limitations of the study are the relatively small sample size and the potential for selection bias since we could only examine patients who underwent radical prostatectomy. CONCLUSIONS: Prostatic ductal adenocarcinoma may be undersampled at TRUS-guided biopsy and in this study was under-reported in routine clinical practice. This highlights the importance of increased awareness of ductal adeoncarcinoma and the need for clear diagnostic criteria. These findings have significant clinical impact especially when determining candidacy for active surveillance protocols.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".