1714 COMPARISON OF MOLECULAR MARKERS, SUB-STAGE AND THE EORTC RISK-SCORE TO PREDICT CLINICAL OUTCOME OF PT1 BLADDER CANCER
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Résumé
You have accessJournal of UrologyBladder Cancer: Invasive/Metastatic Disease II1 Apr 20101714 COMPARISON OF MOLECULAR MARKERS, SUB-STAGE AND THE EORTC RISK-SCORE TO PREDICT CLINICAL OUTCOME OF PT1 BLADDER CANCER Bas van Rhijn, Theo van der Kwast, Bharati Bapat, Peter Bostrom, Neil Fleshner, Madelon van der Aa, Liyang Liu, Chris Bangma, Michael Jewett, Ellen Zwarthoff, and Alexandre Zlotta Bas van RhijnBas van Rhijn Toronto, Canada , Theo van der KwastTheo van der Kwast Toronto, Canada , Bharati BapatBharati Bapat Toronto, Canada , Peter BostromPeter Bostrom Toronto, Canada , Neil FleshnerNeil Fleshner Toronto, Canada , Madelon van der AaMadelon van der Aa Rotterdam, Netherlands , Liyang LiuLiyang Liu Toronto, Canada , Chris BangmaChris Bangma Rotterdam, Netherlands , Michael JewettMichael Jewett Toronto, Canada , Ellen ZwarthoffEllen Zwarthoff Rotterdam, Netherlands , and Alexandre ZlottaAlexandre Zlotta Toronto, Canada View All Author Informationhttps://doi.org/10.1016/j.juro.2010.02.1561AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES We evaluated the impact of sub-stage, clinico-pathological parameters and 4 molecular markers on the clinical outcome of primary pT1 bladder cancer (BC) treated with BCG. METHODS The slides of 129 primary BC from Rotterdam, NL (n=60) and Toronto, Canada (n=69) were reviewed and the pT1 diagnosis was confirmed. Sub-staging was done in two separate rounds, using a new system, i.e. pT1micro-invasive (pT1m) and pT1extensive-invasive (pT1e) 1, and according to invasion of the muscularis mucosae (pT1a/pT1b/pT1c). Uni- and multivariate analyses for recurrence and progression were performed with clinical- (size, multiplicity, hospital, gender, age), pathological- (sub-stage, CIS, grade1973 & 2004) and molecular markers (FGFR3 mutation and MIB-1, P53, P27 expression). EORTC risk-scores for recurrence and progression were calculated. 2 RESULTS Median follow-up was 6.5 years (range 0.3-21.6), 24/129 patients were female. CIS was found in 45 (35%) cases. The EORTC score for recurrence was intermediate in 122/129 (95%), 7 cases were high risk. The EORTC score for progression was intermediate in 16 cases, 113/129 (88%) were high risk. Forty-two patients remained recurrence-free (33%). Progression to pT2 or metastasis was observed in 38 (30%) patients. Sub-stage was as follows: 40 pT1m and 89 pT1e; 79 pT1a, 17 pT1b and 33 pT1c. We found 37 FGFR3 mutations and aberrant expression of MIB-1, P53 and P27 was found in 85, 69 and 48 BCs, respectively. Significant in univariate analysis for recurrence were multiplicity (P<.001) and CIS (P=.026). In multivariate analysis for recurrence, multiplicity (P<.001, RR 2.0, 95%CI: 1.4-3.0) was the only significant variable. Significant in univariate analysis for progression were gender (P=.036), substage (m/e) (P=.004), substage (a/b/c) (P=.009), CIS (P=.029), FGFR3 (P=.031), MIB-1 (P=.034), P27 (P=.048), MIB-1/P27 (P=.012), FGFR3/MIB-1 (P=.033) and FGFR3/P27 (P=.018). In multivariate analysis for progression, female gender (P=.014, RR 2.7, 95%CI: 1.3-5.8), sub-stage (m/e) (P=.003, RR 2.8, 95%CI: 1.4-5.7) and CIS (P=.015, RR 2.1, 95%CI: 1.2-4.0) were the significant variables. Grade and the EORTC risk-scores were never significant. CONCLUSIONS Multiplicity was the strongest predictor of recurrence while CIS, female gender and sub-stage (pT1m / pT1e) 1 were the most important variables for progression in pT1 bladder cancer. The additional value of molecular markers was modest. The value of the EORTC risk-score was limited. References 1 Hum Pathol2005; 36: 981. Google Scholar 2 Eur Urol2008; 54: 303. Google Scholar © 2010 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 183Issue 4SApril 2010Page: e662 Advertisement Copyright & Permissions© 2010 by American Urological Association Education and Research, Inc.MetricsAuthor Information Bas van Rhijn Toronto, Canada More articles by this author Theo van der Kwast Toronto, Canada More articles by this author Bharati Bapat Toronto, Canada More articles by this author Peter Bostrom Toronto, Canada More articles by this author Neil Fleshner Toronto, Canada More articles by this author Madelon van der Aa Rotterdam, Netherlands More articles by this author Liyang Liu Toronto, Canada More articles by this author Chris Bangma Rotterdam, Netherlands More articles by this author Michael Jewett Toronto, Canada More articles by this author Ellen Zwarthoff Rotterdam, Netherlands More articles by this author Alexandre Zlotta Toronto, Canada More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,019 | 0,004 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».