Genitourinary Pathology Society and International Society of Urological Pathology White Paper on Defining Indolent Prostate Cancer
Bibliographic record
Abstract
A significant subset of well-differentiated prostatic acinar neoplasms with invasive histologic features will not spread outside of the prostate, become symptomatic, or shorten a patient's life even if the tumor is left untreated. Overdiagnosis and overtreatment of these indolent prostate cancers (PCa) remain a significant health care problem despite the improved risk assessment and uptake in acceptance of conservative management. While detection of indolent PCa on an entirely resected prostate is possible, recognition of indolent PCa on a needle biopsy (NBX) cannot be reliably made as Grade Group 1 (GG1) PCa diagnosis on NBX is not always identical to one from radical prostatectomy due to a variety of reasons. Further, some of the initially diagnosed GG1 PCas on NBX and carefully monitored on active surveillance (AS) are later reclassified with higher grades. At the same time, other GG1 PCas never progressed on long-term follow-up while receiving no therapy. The overarching goal of this white paper by the 2 leading uropathology organizations, Genitourinary Pathology Society (GUPS) and International Society of Urological Pathology (ISUP), is to help identify a path toward a more meaningful multidisciplinary solution addressing the pervasive problem of overdiagnosis of indolent PCa and its downstream negative effects. Herein, GUPS and ISUP jointly release statements that address why recognition of indolent PCa cannot be reliably made in NBX and why various contemporary multidisciplinary approaches are needed to help improve the detection of indolent PCa in NBX.
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 | 0.011 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.007 | 0.007 |
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".