583 A POPULATION-BASED COMPETING-RISKS ANALYSIS OF SURVIVAL AFTER NEPHRECTOMY FOR RENAL CELL CARCINOMA
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Résumé
You have accessJournal of UrologyKidney Cancer: Evaluation and Staging I1 Apr 2012583 A POPULATION-BASED COMPETING-RISKS ANALYSIS OF SURVIVAL AFTER NEPHRECTOMY FOR RENAL CELL CARCINOMA Marco Bianchi, Maxine Sun, Quoc-Dien Trinh, Jens Hansen, Zhe Tian, Umberto Capitanio, Alberto Briganti, Shahrokh Shariat, Paul Perrotte, Francesco Montorsi, and Pierre Karakiewicz Marco BianchiMarco Bianchi Milan, Italy More articles by this author , Maxine SunMaxine Sun Montreal, Canada More articles by this author , Quoc-Dien TrinhQuoc-Dien Trinh Detroit, MI More articles by this author , Jens HansenJens Hansen Hamburg, Germany More articles by this author , Zhe TianZhe Tian Montreal, Canada More articles by this author , Umberto CapitanioUmberto Capitanio Milan, Italy More articles by this author , Alberto BrigantiAlberto Briganti Milan, Italy More articles by this author , Shahrokh ShariatShahrokh Shariat New York, NY More articles by this author , Paul PerrottePaul Perrotte Montreal, Canada More articles by this author , Francesco MontorsiFrancesco Montorsi Milan, Italy More articles by this author , and Pierre KarakiewiczPierre Karakiewicz Montreal, Canada More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2012.02.659AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Competing cause of mortality has been examined in patients with localized renal cell carcinoma (RCC). However the effect of tumor grade has not been accounted for. We reassessed this topic in all RCC stages integrating tumor grade. METHODS The Surveillance, Epidemiology, and End Results (SEER) database was used to identify 42090 patients treated with NT between years 1988 and 2008. Patients were stratified in 32 strata according to age groups (≤59, 60-69, 70-79, and ≥80 years), Fuhrman grade (I-II vs. III-IV) and American Joint Committee on Cancer (AJCC) stage which resulted in a total of 32 combinations. Competing risk Poisson analyses were performed to simultaneously assess the rates of CSM and OCM at 5 years after nephrectomy. RESULTS Overall 11153 deaths occurred (27%). Of those, 5554 (50%) were due to CSM events. The risk of CSM and OCM at five years after nephrectomy is illustrated in Figure 1. Several findings were observed. First, amongst low-grade tumors, the highest CSM rates at five years were recorded in the youngest age group (≤59 years) with AJCC stage IV RCC (63%). In contrast, the highest OCM rate at five years were recorded in the oldest age group (≥80 years) with AJCC stage I RCC (33%). Not surprisingly, CSM rates increased with disease stage, while OCM rates increased with age. Second, amongst high-grade tumors, a similar trend was recorded where the highest CSM rate at five years were recorded in the youngest age group with AJCC stage IV RCC (79%), while the highest OCM rate at five years was recorded in the oldest age group with AJCC stage I RCC (44%). Finally, it is also noteworthy tumor grade was not particularly detrimental amongst patients with AJCC stage I RCC, especially in the elderly. For example, the five-year CSM rate in patients aged ≤80 years with AJCC stage I RCC was 7% for low-grade vs. 8% for high-grade disease. In contrast, for the same stage, the five-year CSM rate in patients aged ≤59 years was 2% for low-grade vs. 6% for high-grade disease. CONCLUSIONS Our study provides a valuable graphical aid for prediction of CSM, and OCM, according to patient age, disease stage and grade in patients treated with NT for RCC, and this can help clinicians to better stratify the risk-benefit ratio of NT. © 2012 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 187 Issue 4S April 2012 Page: e238 Advertisement Copyright & Permissions© 2012 by American Urological Association Education and Research, Inc.Metrics Author Information Marco Bianchi Milan, Italy More articles by this author Maxine Sun Montreal, Canada More articles by this author Quoc-Dien Trinh Detroit, MI More articles by this author Jens Hansen Hamburg, Germany More articles by this author Zhe Tian Montreal, Canada More articles by this author Umberto Capitanio Milan, Italy More articles by this author Alberto Briganti Milan, Italy More articles by this author Shahrokh Shariat New York, NY More articles by this author Paul Perrotte Montreal, Canada More articles by this author Francesco Montorsi Milan, Italy More articles by this author Pierre 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 | 0,005 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,004 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 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 ».