My approach to intraductal lesions of the prostate gland
Bibliographic record
Abstract
The morphologically heterogeneous (intra)ductal lesions of the prostate frequently present a diagnostic challenge, particularly when found within prostate needle biopsies. By current convention, all high-grade intra-acinar and intraductal neoplastic lesions of prostatic origin fall under the diagnostic umbrella term: prostatic intraepithelial neoplasm (PIN). Although a long-standing contentious issue, some lesions currently adhering to the diagnostic criteria of PIN may actually represent the intraductal spread of (generally high grade) invasive cancer. Illustrating this fact, the well-described ductal subtype of prostatic adenocarcinoma is frequently associated with conventional-type acinar adenocarcinoma, and has a tendency to propagate within adjacent intact prostatic ducts. Clearly, the misdiagnosis of lesions representing invasive disease as preinvasive has the potential for unfavourable clinical sequelae. As yet, however, many of these lesions have escaped the establishment of reliable morphologic criteria or immunohistochemical differentiation for diagnosis. By defining stringent architectural and cytonuclear features specific for each of these lesions, it may be feasible to separate potentially sinister lesions from the subset of traditional (preinvasive) PIN lesions with limited clinical urgency. This review discusses the (intra)ductal lesions of the prostate, along with their differential diagnoses. Given the current state of knowledge, a pragmatic approach to their effective reporting is outlined, taking into consideration the clinical implications, as well as current guidelines for treatment and follow-up.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.006 |
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".