MP32-10 COMPARATIVE EFFECTIVENESS OF ROBOTIC ASSISTED AND OPEN RADICAL CYSTECTOMY IN CONTEMPORARY COHORTS OF BLADDER CANCER PATIENTS: AN INTERNATIONAL MULTICENTER COLLABORATION
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Résumé
You have accessJournal of UrologyBladder Cancer: Invasive II (MP32)1 Apr 2019MP32-10 COMPARATIVE EFFECTIVENESS OF ROBOTIC ASSISTED AND OPEN RADICAL CYSTECTOMY IN CONTEMPORARY COHORTS OF BLADDER CANCER PATIENTS: AN INTERNATIONAL MULTICENTER COLLABORATION Stefania Zamboni*, Francesco Soria, Romain Mathieu, Evanguelos Xylinas, David D'Andrea, Mohammad Abufaraj, Wei Shen Tan, John D. Kelly, Giuseppe Simone, Michele Gallucci, Anoop Meraney, Suprita Krishna, Badrinath Konety, Francesco Montorsi, Alberto Briganti, Agostino Mattei, Philipp Baumeister, Alessandro Antonelli, Claudio Simeone, Michael Rink, Atiqullah Aziz, Pierre I Karakiewicz, Morgan Rouprêt, Matt Perry, Edward Rowe, Anthony Koupparis, Douglas S Scherr, Guillaume Ploussard, Prasanna Sooriakumaran, Shahrokh F. Shariat, and Marco Moschini Stefania Zamboni*Stefania Zamboni* More articles by this author , Francesco SoriaFrancesco Soria More articles by this author , Romain MathieuRomain Mathieu More articles by this author , Evanguelos XylinasEvanguelos Xylinas More articles by this author , David D'AndreaDavid D'Andrea More articles by this author , Mohammad AbufarajMohammad Abufaraj More articles by this author , Wei Shen TanWei Shen Tan More articles by this author , John D. KellyJohn D. Kelly More articles by this author , Giuseppe SimoneGiuseppe Simone More articles by this author , Michele GallucciMichele Gallucci More articles by this author , Anoop MeraneyAnoop Meraney More articles by this author , Suprita KrishnaSuprita Krishna More articles by this author , Badrinath KonetyBadrinath Konety More articles by this author , Francesco MontorsiFrancesco Montorsi More articles by this author , Alberto BrigantiAlberto Briganti More articles by this author , Agostino MatteiAgostino Mattei More articles by this author , Philipp BaumeisterPhilipp Baumeister More articles by this author , Alessandro AntonelliAlessandro Antonelli More articles by this author , Claudio SimeoneClaudio Simeone More articles by this author , Michael RinkMichael Rink More articles by this author , Atiqullah AzizAtiqullah Aziz More articles by this author , Pierre I KarakiewiczPierre I Karakiewicz More articles by this author , Morgan RouprêtMorgan Rouprêt More articles by this author , Matt PerryMatt Perry More articles by this author , Edward RoweEdward Rowe More articles by this author , Anthony KoupparisAnthony Koupparis More articles by this author , Douglas S ScherrDouglas S Scherr More articles by this author , Guillaume PloussardGuillaume Ploussard More articles by this author , Prasanna SooriakumaranPrasanna Sooriakumaran More articles by this author , Shahrokh F. ShariatShahrokh F. Shariat More articles by this author , and Marco MoschiniMarco Moschini More articles by this author View All Author Informationhttps://doi.org/10.1097/01.JU.0000555883.61031.dfAboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVES: In the last 15 years robotic surgery became the leading approach for treatment of prostate and kidney cancer. Following the success of these procedures, robotic system has been more recently applied to treat bladder cancer (BCa) but sparse data exists regarding the diffusion of robotic radical cystectomy (RARC) and its trend in contemporary patients. Aim of our study is comparing utilization trends and time-changes in perioperative outcomes of RARC using data from a large multicenter collaboration. METHODS: We retrospectively evaluated data from 2,713 patients treated with open radical cystectomy (ORC) and RARC for BCa at 16 American and European institutions between 2006 and 2018. All patients had completed data regarding pre-, intra- e post-operative characteristics. The Kruskal-Wallis test and Chi-square test evaluated differences between continuous and categorical variables, respectively. RESULTS: Overall, 971 (36%) patients underwent RARC and 1,705 (64%) ORC. RARC became the most commonly performed procedure in contemporary patients, with an increase from 14% in 2006-2007 to 58% in 2016-2018 (p<0.001). Patients who underwent RARC were younger than those treated with ORC (median 67 years [IQR: 58-78] vs 68 [IQR: 62-75], p<0.001) and percentage of male was higher (82% vs 79%, p=0.015). Patients who underwent RARC had less advanced T stages (pT≤2: RARC vs ORC, 62 % vs 50%, p<0.001) and lymph node (LN) invasion (23% vs 32%, p<0.001). Despite no significant differences in operation time (RARC vs ORC, median 360 min [IQR 300-425] vs. 360 min [300-420], p=0.3) patients treated with RARC had more LN removed (median 19 [IQR 12-27] vs 17 [IQR 10-24], p=0.001). Blood loss was significantly lower for RARC (400 ml [IQR 200-600] vs 800 [IQR 500-1300], p=0.001) as well as length of stay (9 days [IQR 7-12] vs 19 [IQR 13-26], p=0.001). No differences were found in early reoperation rates (p=0.1) or perioperative mortality (p=0.6). Patients treated with RARC were more likely to be readmitted (19% vs 13%, p=0.002). All perioperative outcomes remained stable over the study period. CONCLUSIONS: The use of RARC is constantly increasing overtaking at these selected centers, ORC. In the last decade perioperative outcomes remained substantially unchanged. We confirmed the lower blood loss and shorter length of stay of RARC compared to ORC. Studies need to reveal whether these quality criteria translate into sustainable long-term quality and quantity of life benefits. Source of Funding: none Lucerne, Switzerland; Vienna, Austria; Paris, France; Vienna, Austria; London, United Kingdom; Rome, Italy; Hartford, CT; Minneapolis, MN; Milan, Italy; Lucerne, Switzerland; Brescia, Italy; Hamburg, Germany; Rostock, Germany; Montreal, Canada; Paris, France; London, United Kingdom; Bristol, United Kingdom; New York, NY; Toulouse, France; London, United Kingdom; Vienna, Austria© 2019 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 201Issue Supplement 4April 2019Page: e446-e447 Advertisement Copyright & Permissions© 2019 by American Urological Association Education and Research, Inc.MetricsAuthor Information Stefania Zamboni* More articles by this author Francesco Soria More articles by this author Romain Mathieu More articles by this author Evanguelos Xylinas More articles by this author David D'Andrea More articles by this author Mohammad Abufaraj More articles by this author Wei Shen Tan More articles by this author John D. Kelly More articles by this author Giuseppe Simone More articles by this author Michele Gallucci More articles by this author Anoop Meraney More articles by this author Suprita Krishna More articles by this author Badrinath Konety More articles by this author Francesco Montorsi More articles by this author Alberto Briganti More articles by this author Agostino Mattei More articles by this author Philipp Baumeister More articles by this author Alessandro Antonelli More articles by this author Claudio Simeone More articles by this author Michael Rink More articles by this author Atiqullah Aziz More articles by this author Pierre I Karakiewicz More articles by this author Morgan Rouprêt More articles by this author Matt Perry More articles by this author Edward Rowe More articles by this author Anthony Koupparis More articles by this author Douglas S Scherr More articles by this author Guillaume Ploussard More articles by this author Prasanna Sooriakumaran More articles by this author Shahrokh F. Shariat More articles by this author Marco Moschini More articles by this author Expand All 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 | 0,024 | 0,038 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,004 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| 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) | 0,002 | 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 ».