The ISUP system of staging, grading and classification of renal cell neoplasia
Bibliographic record
Abstract
There have been significant changes in the staging, classification and grading of renal cell neoplasia in recent times. Major changes have occurred in our understanding of extra-renal extension by renal cell cancer and how gross specimens must be handled to optimally display extra-renal spread. Since the 1981 World Health Organization (WHO) classification of renal tumors, in which only a handful of different entities were reported, many new morphological types have been described in the literature, resulting in 50 different entities reported in the 2004 WHO classification. Since 2004, further new entities have been recognized and reported necessitating an update of the renal tumor classification. There have also been numerous grading systems for renal cell carcinoma with Fuhrman grading, the most widely used system. In recent times, the prognostic value and the applicability of the Fuhrman grading system in practice has been shown to be, at best, suboptimal. To address these issues and to recommend reporting guidelines, the International Society of Urological Pathology (ISUP) undertook a review of adult renal neoplasia through an international consensus conference in Vancouver in 2012. The conduct of the conference was based upon evidence from the literature and the current practice amongst recognized experts in the field. Working groups selected to deal with key topics evaluated current data and identified points of controversy. A pre-meeting survey of the ISUP membership was followed by the consensus conference at which a formal ballot was taken on each key issue. A 65% majority vote was taken as consensus. This review summarizes the outcome and recommendations of this conference with regards to staging, classification and grading of renal cell neoplasia.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".