MP26-15 MOLECULAR SUBTYPING REVEALS LUMINAL BLADDER TUMORS HAVE LOWER RATES OF PATHOLOGICAL UPSTAGING AT RADICAL CYSTECTOMY
Bibliographic record
Abstract
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 ...
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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.
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".