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Record W2590571433 · doi:10.5489/cuaj.4136

Inverted urothelial papilloma: A review of diagnostic pitfalls and clinical management

2017· review· en· W2590571433 on OpenAlexvenueno aff
Mary Katherine Sweeney, Soroush Rais‐Bahrami, Jennifer Gordetsky

Bibliographic record

VenueCanadian Urological Association Journal · 2017
Typereview
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsInverted papillomaMedicinePapillomaPathology

Abstract

fetched live from OpenAlex

Inverted urothelial papilloma (IUP) is a rare, non-invasive endophytic lesion that accounts for 1-2% of urothelial tumours. On cystoscopy, IUP appears as a pedunculated/papillary mass with a smooth surface. On microscopy, IUP has an endophytic growth pattern with the bulk of the tumour covered by a superficial layer of urothelium, which can be hyperplastic or attenuated. The cytology should be bland, with uniform, spindled cells arranged in anastomosing trabeculae and cords with peripheral palisading of basaloid cells. Exophytic papillae and mitotic activity should be absent or focal. Pseudoglandular spaces and squamous metaplasia may also be present. There are distinct molecular differences between IUP and urothelial carcinoma (UC). IUP rarely has mutations of FGFR3, homozygous loss of 9p21, or gain of chromosomes 3, 7, and 17, whereas these mutations are frequently seen in UC. In addition, IUP is much less likely to have TERT mutations compared to UC. Immunohistochemistry can also be helpful in distinguishing the two entities as IUP is typically negative for CK20 and has a low Ki-67 proliferation index. Positivity for p53 may be seen in a minority of IUP. IUP can recur and be seen in association with UC. Distinguishing IUP from UC can be difficult due to the similarity between the two entities both on cystoscopy and histology, as up to 25% of UCs will also have inverted growth. Given the morphologic variants of IUP and UC, it is possible for a diagnostic error to occur, which can significantly impact patient management.

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 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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.955
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.074
GPT teacher head0.374
Teacher spread0.300 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations22
Published2017
Admission routes1
Has abstractyes

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