MP84-08 PATHOLOGICAL UPSTAGING OF CLINICAL T1 RENAL CELL CARCINOMA: A MULTI-INSTITUTIONAL ANALYSIS OF OUTCOMES
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Résumé
You have accessJournal of UrologyKidney Cancer: Surgical Therapy VII1 Apr 2015MP84-08 PATHOLOGICAL UPSTAGING OF CLINICAL T1 RENAL CELL CARCINOMA: A MULTI-INSTITUTIONAL ANALYSIS OF OUTCOMES Jasmir Nayak, Premal Patel, Jennifer Bjazevic, Olli Saarela, Zhihui Liu, Anil Kapoor, Simon Tanguay, Antonio Finelli, Ricardo Rendon, Ron Moore, Rodney Breau, Jun Kawakami, Peter Black, and Darrel Drachenberg Jasmir NayakJasmir Nayak More articles by this author , Premal PatelPremal Patel More articles by this author , Jennifer BjazevicJennifer Bjazevic More articles by this author , Olli SaarelaOlli Saarela More articles by this author , Zhihui LiuZhihui Liu More articles by this author , Anil KapoorAnil Kapoor More articles by this author , Simon TanguaySimon Tanguay More articles by this author , Antonio FinelliAntonio Finelli More articles by this author , Ricardo RendonRicardo Rendon More articles by this author , Ron MooreRon Moore More articles by this author , Rodney BreauRodney Breau More articles by this author , Jun KawakamiJun Kawakami More articles by this author , Peter BlackPeter Black More articles by this author , and Darrel DrachenbergDarrel Drachenberg More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2015.02.1975AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES It has been suggested that the survival among those with clinical T1 renal cell carcinoma (RCC) is unaffected by pathological upstaging and perhaps nephron-sparring surgery should not be dissuaded by concerns for this occurrence. We evaluated the early oncological outcomes for patients upstaged from cT1 to pT2/T3a RCC treated by partial (PN) or radical nephrectomy (RN). METHODS The Canadian Kidney Cancer Information System is a prospectively maintained database for patients diagnosed with RCC from 15 Canadian institutions. Patients surgically treated for non-metastatic, cT1 RCC between 2009-2014 were evaluated. Upstaging was defined as pT2/T3a disease on final pathology. Our primary outcome was disease progression (recurrence or metastatic disease). Multi-variate Cox regression analysis (MVA) identified predictors for progression while logistic regression was used to predict upstaging. Kaplan-Meir methods estimated survival. RESULTS Of 1187 patients with cT1 disease, 862 (73%) underwent PN and 325 (27%) RN. Median follow up was 18 months. 121 (10%) patients were upstaged; 55 (6%) treated by PN and 66 (20%) treated by RN. The 24-month progression-free survival (PFS) was 88% in those upstaged compared with 95% in those not upstaged (p<0.001). Sub-stratifying by surgical approach, upstaged compared with non-upstaged patients had lower PFS rates for both PN (90% vs 95%, P<0.001) and RN (86% vs 95%, p=0.001). The difference in 24 month PFS among upstaged patients treated by PN compared with RN was not significant. The median time to progression was 48 months in upstaged patients and not-reached in those without upstaging. Controlling for age, gender, year of surgery, histology, tumor size and surgical approach, pathological upstaging was independently associated with PFS (HR 2.40, 95% CI 1.23-4.67). Increasing age (OR 1.03, 95% CI 1.01-1.05) and tumor size (OR 1.87, 95% CI 1.62-2.15) were associated with a risk of pathological upstaging. CONCLUSIONS Pathological upstaging is associated with inferior oncological outcomes at short-term follow-up, irrespective of surgical approach. These findings highlight the importance of accurate clinical staging to facilitate informed decision making among patients with clinical T1 RCC considering treatment options. © 2015 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 193Issue 4SApril 2015Page: e1060-e1061 Advertisement Copyright & Permissions© 2015 by American Urological Association Education and Research, Inc.MetricsAuthor Information Jasmir Nayak More articles by this author Premal Patel More articles by this author Jennifer Bjazevic More articles by this author Olli Saarela More articles by this author Zhihui Liu More articles by this author Anil Kapoor More articles by this author Simon Tanguay More articles by this author Antonio Finelli More articles by this author Ricardo Rendon More articles by this author Ron Moore More articles by this author Rodney Breau More articles by this author Jun Kawakami More articles by this author Peter Black More articles by this author Darrel Drachenberg 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 | 0,002 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
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 ».