Recent developments in eosinophilic renal neoplasms: what's new, true and important?
Bibliographic record
Abstract
We focus in this review on the latest developments on several eosinophilic renal entities, aiming to provide an update on this topic that was previously addressed by the Genitourinary Pathology Society in their consensus papers on existing renal entities, and on novel, emerging, and provisional renal entities, and in the World Health Organization 2022 Classification of Renal Cell Tumours (5th Edition). The scope of this review includes an update on more recently described eosinophilic renal entities, including low-grade oncocytic renal tumour (LOT), eosinophilic vacuolated tumour (EVT), folliculin (FLCN) mutated tumour, succinate dehydrogenase (SDH)-deficient renal cell carcinoma, epithelioid angiomyolipoma/epithelioid PEComa (eAML/ePEComa), eosinophilic solid and cystic renal cell carcinoma (ESC RCC), anaplastic lymphoma kinase (ALK)-rearranged RCC, fumarate hydratase (FH)-deficient RCC, papillary renal neoplasm of reversed polarity (PRNRP), tubulocystic RCC (TC-RCC), and thyroid-like follicular carcinoma of kidney (TLFCK). These renal entities fall within the spectrum of eosinophilic renal tumours, in addition to the more common ones with eosinophilic features that will not be covered in this review, such as clear cell renal RCC, papillary RCC, chromophobe RCC, TFE3 rearranged RCC, and TFEB-altered RCC. Pathologists need to consider these less common renal entities in the differential of any eosinophilic renal tumour to be able to diagnose them for the benefit of their patients. The recent developments and acquired knowledge on newer renal entities with eosinophilic cytoplasm opened insights into the clinical, pathological, immunohistochemical, molecular, epidemiological aspects, and the prognosis of these entities. We emphasize the role of routine morphology, aided by appropriate and select immunohistochemistry, as essential keys for diagnosing eosinophilic renal tumours.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".