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Record W3199946068 · doi:10.1053/j.semdp.2021.09.004

Undifferentiated and dedifferentiated urological carcinomas: lessons learned from the recent developments

2021· review· en· W3199946068 on OpenAlex
Abbas Agaimy, Arndt Hartmann, Kiril Trpkov, Ondřej Hes

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSeminars in Diagnostic Pathology · 2021
Typereview
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsUniversity of CalgaryCalgary Laboratory Services
Fundersnot available
KeywordsPathologyImmunophenotypingBiologyVimentinCarcinomaHematopathologyImmunohistochemistryMedicineCytogeneticsImmunologyFlow cytometry

Abstract

fetched live from OpenAlex

Loss of the morphological and immunophenotypic characteristics of a neoplasm is a well-known phenomenon in surgical pathology and occurs across different tumor types in almost all organs. This process may be either partial, characterized by transition from well differentiated to undifferentiated tumor component (=dedifferentiated carcinomas) or complete (=undifferentiated carcinomas). Diagnosis of undifferentiated carcinoma is significantly influenced by the extent of sampling. Although the concept of undifferentiated and dedifferentiated carcinoma has been well established for other organs (e.g. endometrium), it still has not been fully defined for urological carcinomas. Accordingly, undifferentiated/ dedifferentiated genitourinary carcinomas are typically lumped into the spectrum of poorly differentiated, sarcomatoid, or unclassified (NOS) carcinomas. In the kidney, dedifferentiation occurs across all subtypes of renal cell carcinoma (RCC), but certain genetically defined RCC types (SDH-, FH- and PBRM1- deficient RCC) seem to have inherent tendency to dedifferentiate. Histologically, the undifferentiated component displays variable combination of four patterns: spindle cells, pleomorphic giant cells, rhabdoid cells, and undifferentiated monomorphic cells with/without prominent osteoclastic giant cells. Any of these may occasionally be associated with heterologous mesenchymal component/s. Their immunophenotype is often simple with expression of vimentin and variably pankeratin or EMA. Precise subtyping of undifferentiated (urothelial versus RCC and the exact underlying RCC subtype) is best done by thorough sampling supplemented as necessary by immunohistochemistry (e.g. FH, SDHB, ALK) and/ or molecular studies. This review discusses the morphological and molecular genetic spectrum and the recent develoments on the topic of dedifferentiated and undifferentiated genitourinary carcinomas.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.962
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.132
GPT teacher head0.356
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it