Grading of prostate cancer: a work in progress
Bibliographic record
Abstract
Grading of prostate cancer has evolved substantially over time, not least because of major changes in diagnostic approach and concomitant shifts from late- to early-stage detection since the adoption of PSA testing from the late 1980s. After the conception of the architecture-based nine-tier Gleason grading system more than 50 years ago, several changes were made in order to increase its prognostic impact, to reduce interobserver variation and to improve concordance between prostate needle biopsy and radical prostatectomy grading. This eventually resulted in the current five-tier grading system, with a much more detailed description of the individual architectural patterns constituting the remaining three Gleason patterns (i.e. grades 3-5). Nevertheless, there is room for improvement. For instance, distinction of common grade 4 subpatterns such as ill-formed and fused glands from the grade 3 pattern is challenging, blurring the division between low-risk patients who could be eligible for deferred therapy and those who need curative therapy. The last few years have witnessed the publication of several studies on the prognostic impact of individual architectural subpatterns showing that, in particular, the cribriform pattern exceeded the prognostic impact of other grade 4 subpatterns. This review provides an overview of the changes in prostate cancer grading over time and provides a thorough description of the various Gleason subpatterns, the current evidence of their prognostic impact and areas of contention. Potential practical ways for improvements of the current grading system are also put forward.
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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".