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MP26-15 MOLECULAR SUBTYPING REVEALS LUMINAL BLADDER TUMORS HAVE LOWER RATES OF PATHOLOGICAL UPSTAGING AT RADICAL CYSTECTOMY

2019· article· en· W2941005461 on OpenAlexaboutno aff
Y. Lotan, Stephen A. Boorjian, Jingbin Zhang, Trinity J. Bivalacqua, Seth P. Lerner, Sima P. Porten, Thomas M. Wheeler, Ryan Hutchinson, Franto Francis, Marguerite du Plessis, Elai Davicioni, Robert S. Svatek, Peter C. Black, Ewan A. Gibb

Bibliographic record

VenueThe Journal of Urology · 2019
Typearticle
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsCystectomySubtypingMedicinePathologicalUrologyBladder cancerPathologyInternal medicineCancer

Abstract

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You have accessJournal of UrologyBladder Cancer: Invasive I (MP26)1 Apr 2019MP26-15 MOLECULAR SUBTYPING REVEALS LUMINAL BLADDER TUMORS HAVE LOWER RATES OF PATHOLOGICAL UPSTAGING AT RADICAL CYSTECTOMY Yair Lotan*, Stephen Boorjian, Jingbin Zhang, Trinity Bivalacqua, Seth Lerner, Sima Porten, Thomas Wheeler, Ryan Hutchinson, Franto Francis, Marguerite du Plessis, Elai Davicioni, Robert Svatek, Peter Black, and Ewan Gibb Yair Lotan*Yair Lotan* More articles by this author , Stephen BoorjianStephen Boorjian More articles by this author , Jingbin ZhangJingbin Zhang More articles by this author , Trinity BivalacquaTrinity Bivalacqua More articles by this author , Seth LernerSeth Lerner More articles by this author , Sima PortenSima Porten More articles by this author , Thomas WheelerThomas Wheeler More articles by this author , Ryan HutchinsonRyan Hutchinson More articles by this author , Franto FrancisFranto Francis More articles by this author , Marguerite du PlessisMarguerite du Plessis More articles by this author , Elai DavicioniElai Davicioni More articles by this author , Robert SvatekRobert Svatek More articles by this author , Peter BlackPeter Black More articles by this author , and Ewan GibbEwan Gibb More articles by this author View All Author Informationhttps://doi.org/10.1097/01.JU.0000555680.51731.d0AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVES: Upstaging of bladder cancer from precystectomy clinical stage ≤T2 to non-organ confined pathologic stage ≥T3 or N+ at radical cystectomy (RC) is common and can significantly increase the risk of cancer-specific mortality (CSM). We assessed the ability of a genomic subtyping classifier (GSC) to predict pathological upstaging in a multi-institutional cohort of patients with clinical T1-T2 bladder cancer treated with RC. METHODS: A cohort of 206 patients with clinical high-grade, organ-confined (cT1-T2, N0M0) treated with RC and bilateral PLND without neoadjuvant chemotherapy (NAC) was selected from the registries of 7 academic hospitals. Precystectomy bladder tumor transurethral resection FFPE specimens were submitted for genomic testing with the Decipher Bladder assay (GenomeDx, San Diego, CA). Uni- and multi-variable logistic regression analysis (UVA/MVA) were used to evaluate a locked GSC for upstaging, defined as pT3/T4 and/or pTanyN1-3 disease at RC. Cumulative incidence of CSM was calculated using Fine-Gray competing risks. RESULTS: Upstaging to non-organ confined disease (≥T3 and/or ≥N1) occurred in 23% of cT1 and 57% of cT2 cases, respectively. Stratifying for clinical stage, fewer patients with luminal tumors were upstaged to ≥pT3 compared to non-luminal tumors (M-H p-value = 0.002; cT1: 13% vs 34%, cT2: 34% vs 58%, respectively). On UVA and MVA, non-luminal patients were significantly more likely to upstage (≥pT3) at RC compared to luminal patients (p<0.001 for both). Conversely, rates of upstaging to ≥N1 disease were similar when considering clinical stage and subtype. Rates of upstaging to ≥N1 at cT1 were 13% for both luminal and non-luminal patients (p>0.9). Similarly, for cT2, upstaging to ≥N1 was 15% for luminal and 23% for non-luminal patients (p=0.56). Luminal patients also trended toward having better prognosis as determined by lower CSM rates compared to non-luminal patients (p=0.061). CONCLUSIONS: Molecular subtyping revealed luminal tumors have lower rates of upstaging compared to non-luminal tumors. Combined with previous reports that the benefit of NAC may be greatest in basal tumors, these data suggest that subtyping may have utility in identifying higher risk patients who could be prioritized for NAC. Nevertheless, approximately one-third of luminal tumors with cT2 tumors are upstaged to non-organ confined disease. These patients should continue to receive NAC until further studies evaluate the implications of immediate cystectomy. Source of Funding: Trancriptome profiling was funded by GenomeDx Inc. Dallas, TX; Rochester, MN; Vancouver, Canada; Baltimore, MD; Houston, TX; San Francisco, CA; Houston, TX; Dallas, TX; Vancouver, Canada; San Diego, CA; San Antonio, TX; Vancouver, Canada© 2019 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 201Issue Supplement 4April 2019Page: e358-e359 Advertisement Copyright & Permissions© 2019 by American Urological Association Education and Research, Inc.MetricsAuthor Information Yair Lotan* More articles by this author Stephen Boorjian More articles by this author Jingbin Zhang More articles by this author Trinity Bivalacqua More articles by this author Seth Lerner More articles by this author Sima Porten More articles by this author Thomas Wheeler More articles by this author Ryan Hutchinson More articles by this author Franto Francis More articles by this author Marguerite du Plessis More articles by this author Elai Davicioni More articles by this author Robert Svatek More articles by this author Peter Black More articles by this author Ewan Gibb More articles by this author Expand All Advertisement PDF downloadLoading ...

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.012
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.004

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 head0.015
GPT teacher head0.285
Teacher spread0.269 · 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 source (direct Gemma or distilled Codex), 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".

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Citations1
Published2019
Admission routes1
Has abstractyes

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