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Comprehensive and epidemiological characterization of urachal adenocarcinoma: A pan-Canadian collaboration.

2019· article· en· W2921002154 on OpenAlexaffabout
Wiam Belkaïd, Zineb Hamilou, Denis Soulières, Christina M. Canil, Paweł Zalewski, Daniel Yick Chin Heng, Vitor Da Silva, Mathias Castonguay, Bertrand Routy, Normand Blais

Bibliographic record

VenueJournal of Clinical Oncology · 2019
Typearticle
Languageen
FieldMedicine
TopicUrinary and Genital Oncology Studies
Canadian institutionsUniversity of CalgaryRegional Municipality of DurhamUniversity of OttawaOttawa HospitalCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineCystectomyStage (stratigraphy)Bladder cancerDiseaseMalignancyEpidemiologyInternal medicineOncologyCancer

Abstract

fetched live from OpenAlex

516 Background: Urachal cancer is a rare form of urothelial cancer representing 0,1-0,2% of bladder cancers. The exact underlying cause of urachal cancer is still widely unknown and there is much speculation on multiple factors such as genetic and environmental ones that may play a role. Moreover, given the lack of treatment consensus, we proposed the first study that assesses the clinical, genetic and molecular features of this disease in Canada. Methods: This ongoing study is recruiting in Canadian centers from the year 2005 onwards. The clinical database is constructed using the hospital electronic medical file. In addition, pathological tissues are centralized for molecular and genetic analysis. Results: To this date, 15 patients were included, 12 males and 3 females. Median age was of 49 years old with a disease distribution of Stage II (4), Stage III (3) and Stage IV (4). 8/15 patients developed metastasis after initial cystectomy in the lungs (n = 7), peritoneum (n = 2), lymph nodes (n = 4), and bone (1). Median survival of all patients was 23 months. Metastatic patients after cystectomy had a shorter overall survival (OS) of 21 months compared to non-metastatic patients (OS – not reached). The majority of metastatic patients (6/8) died of their underlying malignancy. Conclusions: This study is an ongoing country-wide effort to expand knowledge of this poorly studied disease. With ongoing accrual, the clinical features will be better defined and further molecular characterization will be performed to better predict response to therapy.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.326

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.137
GPT teacher head0.444
Teacher spread0.306 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations1
Published2019
Admission routes2
Has abstractyes

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