1787 THE EFFECT OF NODAL CODING SCHEMES ON CANCER-SPECIFIC MORTALITY AFTER CYTOREDUCTIVE NEPHRECTOMY
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Résumé
You have accessJournal of UrologyKidney Cancer: Advanced I1 Apr 20121787 THE EFFECT OF NODAL CODING SCHEMES ON CANCER-SPECIFIC MORTALITY AFTER CYTOREDUCTIVE NEPHRECTOMY Quoc-Dien Trinh, Jan Schmitges, Jesse D. Sammon, Khurshid R. Ghani, Maxine Sun, Jens Hansen, Wooju Jeong, Marco Bianchi, Jay Jhaveri, Shyam Sukumar, Paul Perrotte, Claudio Jeldres, Piyush K. Agarwal, Craig G. Rogers, James O. Peabody, Shahrokh F. Shariat, Mani Menon, and Pierre I. Karakiewicz Quoc-Dien TrinhQuoc-Dien Trinh Detroit, MI More articles by this author , Jan SchmitgesJan Schmitges Hamburg, Germany More articles by this author , Jesse D. SammonJesse D. Sammon Detroit, MI More articles by this author , Khurshid R. GhaniKhurshid R. Ghani Detroit, MI More articles by this author , Maxine SunMaxine Sun Montreal, Canada More articles by this author , Jens HansenJens Hansen Hamburg, Germany More articles by this author , Wooju JeongWooju Jeong Detroit, MI More articles by this author , Marco BianchiMarco Bianchi Montreal, Canada More articles by this author , Jay JhaveriJay Jhaveri Detroit, MI More articles by this author , Shyam SukumarShyam Sukumar Detroit, MI More articles by this author , Paul PerrottePaul Perrotte Montreal, Canada More articles by this author , Claudio JeldresClaudio Jeldres Montreal, Canada More articles by this author , Piyush K. AgarwalPiyush K. Agarwal Detroit, MI More articles by this author , Craig G. RogersCraig G. Rogers Detroit, MI More articles by this author , James O. PeabodyJames O. Peabody Detroit, MI More articles by this author , Shahrokh F. ShariatShahrokh F. Shariat New York, NY More articles by this author , Mani MenonMani Menon Detroit, MI More articles by this author , and Pierre I. KarakiewiczPierre I. Karakiewicz Montreal, Canada More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2012.02.1818AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Relatively few reports have described the outcomes of patients with node-positive renal cell carcinoma (RCC) in the presence of distant metastases. We examined the outcomes of these patients in a large population-based cohort of patients and examined the ability of standard risk factors to predict cancer-specific mortality (CSM). METHODS Using the Surveillance, Epidemiology, and End Results database, a total of 619 RCC patients with nodal and distant metastases undergoing cytoreductive nephrectomy were identified. Univariable and multivariable analyses addressed CSM with the intent of identifying independent predictors of CSM in this cohort of patients. Specifically, we examined the effect of the number of removed nodes (NRN), the number of positive nodes (NPN) and the percentage of positive nodes (PPN) on CSM. RESULTS Actuarial survival estimates demonstrated that 40.2, 23.5 and 11.5% of patients survived at 12, 24 and 60 months after nephrectomy. In Kaplan-Meier analyses, NRN failed to clearly discriminate between recorded CSM rates (log rank p=0.9). Discrimination was noted when CSM was stratified according to NPN (log rank p=0.002) and PPN (log rank p=0.003). In multivariable analyses, year of diagnosis, histological subtype and PPN were independent predictors of CSM. CONCLUSIONS Our data indicate that PPN is an independent predictor of CSM in patients with nodal and distant metastases undergoing cytoreductive nephrectomy. Consequently, PPN warrants consideration in future prognostic schemes. © 2012 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 187Issue 4SApril 2012Page: e721 Advertisement Copyright & Permissions© 2012 by American Urological Association Education and Research, Inc.MetricsAuthor Information Quoc-Dien Trinh Detroit, MI More articles by this author Jan Schmitges Hamburg, Germany More articles by this author Jesse D. Sammon Detroit, MI More articles by this author Khurshid R. Ghani Detroit, MI More articles by this author Maxine Sun Montreal, Canada More articles by this author Jens Hansen Hamburg, Germany More articles by this author Wooju Jeong Detroit, MI More articles by this author Marco Bianchi Montreal, Canada More articles by this author Jay Jhaveri Detroit, MI More articles by this author Shyam Sukumar Detroit, MI More articles by this author Paul Perrotte Montreal, Canada More articles by this author Claudio Jeldres Montreal, Canada More articles by this author Piyush K. Agarwal Detroit, MI More articles by this author Craig G. Rogers Detroit, MI More articles by this author James O. Peabody Detroit, MI More articles by this author Shahrokh F. Shariat New York, NY More articles by this author Mani Menon Detroit, MI More articles by this author Pierre I. Karakiewicz Montreal, 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 | 0,002 | 0,020 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 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 | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 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 ».