1027 A POPULATION-BASED COMPETING-RISKS ANALYSIS OF THE SURVIVAL OF PATIENTS TREATED WITH RADICAL CYSTECTOMY FOR BLADDER CANCER
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Résumé
You have accessJournal of UrologyBladder Cancer: Staging1 Apr 20101027 A POPULATION-BASED COMPETING-RISKS ANALYSIS OF THE SURVIVAL OF PATIENTS TREATED WITH RADICAL CYSTECTOMY FOR BLADDER CANCER Giovanni Lughezzani, Claudio Jeldres, Lars Budaus, Maxine Sun, Rodolphe Thuret, Shahrokh F. Shariat, Daniel Liberman, Hugues Widmer, Philippe Arjane, Markus Graefen, Seth P. Lerner, Paul Perrotte, Francesco Montorsi, and Pierre I. Karakiewicz Giovanni LughezzaniGiovanni Lughezzani Milano, Italy More articles by this author , Claudio JeldresClaudio Jeldres Montreal, Canada More articles by this author , Lars BudausLars Budaus Hamburg, Germany More articles by this author , Maxine SunMaxine Sun Montreal, Canada More articles by this author , Rodolphe ThuretRodolphe Thuret Montpellier, France More articles by this author , Shahrokh F. ShariatShahrokh F. Shariat Montreal, Canada More articles by this author , Daniel LibermanDaniel Liberman Montreal, Canada More articles by this author , Hugues WidmerHugues Widmer Montreal, Canada More articles by this author , Philippe ArjanePhilippe Arjane Montreal, Canada More articles by this author , Markus GraefenMarkus Graefen Hamburg, Germany More articles by this author , Seth P. LernerSeth P. Lerner Houston, TX More articles by this author , Paul PerrottePaul Perrotte Montreal, Canada More articles by this author , Francesco MontorsiFrancesco Montorsi Milano, Italy 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.2010.02.2062AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES The radical cystectomy (RC) population is very heterogeneous with respect of cancer-specific (CSM) and other-cause mortality (OCM). Comorbidities and comorbidities-associated events represent very important causes of mortality in RC patients. We examined the rates of CSM and OCM in a population-based RC cohort. METHODS We identified 11260 patients treated with RC for urothelial carcinoma of the urinary bladder between 1988 and 2006 within 17 Surveillance, Epidemiology and End Results database. Patients were stratified into 20 age-tumor stage categories. Poisson regression models were fitted to obtain estimates of CSM and OCM mortality rates at specific time points after RC. RESULTS After stratification according to disease stage and patient age, CSM resulted as the main cause of mortality in all patients strata, Nonetheless, at 5 years after RC between 8.5 and 27.1% of deaths were attributable to OCM. The three most common causes of OCM were heart disease, other malignancies and chronic obstructive pulmonary disease. The most prominent effect on CSM was exerted by locally-advanced BCa stages. Conversely, age was the main determinant of OCM. Interestingly, even after adjusting for bladder cancer pathologic stage, CSM was higher in older individuals than in younger patients. CONCLUSIONS Our model represents a valuable tool capable of predicting OCM and CSM according to disease stage and patient age. The model results can help clinicians to better stratify the risk-benefit ratio of RC. Hopefully, this tool will be integrated into patient counseling and informed consent process prior to RC in patients who represent surgical candidates. © 2010 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 183Issue 4SApril 2010Page: e399 Advertisement Copyright & Permissions© 2010 by American Urological Association Education and Research, Inc.MetricsAuthor Information Giovanni Lughezzani Milano, Italy More articles by this author Claudio Jeldres Montreal, Canada More articles by this author Lars Budaus Hamburg, Germany More articles by this author Maxine Sun Montreal, Canada More articles by this author Rodolphe Thuret Montpellier, France More articles by this author Shahrokh F. Shariat Montreal, Canada More articles by this author Daniel Liberman Montreal, Canada More articles by this author Hugues Widmer Montreal, Canada More articles by this author Philippe Arjane Montreal, Canada More articles by this author Markus Graefen Hamburg, Germany More articles by this author Seth P. Lerner Houston, TX More articles by this author Paul Perrotte Montreal, Canada More articles by this author Francesco Montorsi Milano, Italy 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 | 0,005 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,003 |
| Bibliométrie | 0,001 | 0,002 |
| 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) | 0,008 | 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 ».