International Society of Urological Pathology Consensus on Cancer Precursor Lesions. Working Group 1
Bibliographic record
Abstract
Working Group 1 at ISUP's Cancer Precursors meeting (September 2024) evaluated 5 putative precursors of invasive prostate cancer: high-grade prostatic intraepithelial neoplasia (HGPIN), intraductal carcinoma (IDC), atypical intraductal proliferation (AIP), atypical adenomatous hyperplasia (AAH)/adenosis, and proliferative inflammatory atrophy (PIA). Objectives were to compile recent evidence, interrogate current practices, and vote on recommendations, with 67% approval defined as consensus. Consensus was reached against the reporting of the low-grade form of PIN. HGPIN need not be reported when concomitant cancer or atypical small acinar proliferation suspicious for cancer exists adjacent to it, for biopsy or prostatectomy specimens. Finally, while the clinical significance of unifocal HGPIN in biopsies remains uncertain, there is stronger evidence for multifocal isolated HGPIN as a predictor of subsequent cancer detection. By consensus, multifocal HGPIN should continue being reported. Slight refinement was achieved regarding IDC criteria. The consensus opinion was that a dense cribriform to solid proliferation need not demonstrate marked nuclear atypia/ pleomorphism to qualify as IDC. The inverse scenario of marked atypia without dense cribriform/solid proliferation fell just short (65%) of consensus for IDC. Redesignating cribriform HGPIN as AIP achieved consensus. AIP found alone or with grade group 1 cancer warrants an explanatory comment. However, agreement was not attained to report AIP in the presence of invasive cancer, in either needle biopsy or prostatectomy. Finally, the optional reporting of PIA or AAH/adenosis in biopsies as pertinent negatives both fell short of consensus. This guidance should help pathologists standardize reporting, staying focused on the clinically actionable aspects of these lesions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.030 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.009 | 0.009 |
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".