MP62-03 ROBOT ASSISTED RADICAL PROSTATECTOMY IN HIGH RISK PROSTATE CANCER
Notice bibliographique
Résumé
You have accessJournal of UrologyProstate Cancer: Localized V1 Apr 2015MP62-03 ROBOT ASSISTED RADICAL PROSTATECTOMY IN HIGH RISK PROSTATE CANCER Benjamin Katz, Sue-Jean Yu, Andrew Lightfoot, Giovanni Greaves, Elton Llukani, Alice McGill, Kelly Monahan, and David Lee Benjamin KatzBenjamin Katz More articles by this author , Sue-Jean YuSue-Jean Yu More articles by this author , Andrew LightfootAndrew Lightfoot More articles by this author , Giovanni GreavesGiovanni Greaves More articles by this author , Elton LlukaniElton Llukani More articles by this author , Alice McGillAlice McGill More articles by this author , Kelly MonahanKelly Monahan More articles by this author , and David LeeDavid Lee More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2015.02.2377AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Robot assisted radical prostatectomy (RARP) in the treatment paradigm of high-risk prostate cancer has not been well studied to date. Punnen et al reported similar results for open retropubic radical prostatectomy (RRP) as compared to RARP in men with high-risk prostate cancer. RRP utilized as monotherapy for Gleason ≥8 in 188 men showed a disease-free survival, at 5 and 7 years, of 71% and 55% respectively. Our goal was to evaluate our experience in all patients with high-risk prostate cancer undergoing RARP at our institution. METHODS We performed a single-institution, single-surgeon review of 3,433 patients who underwent RARP from 2005 to 2014. Patients were identified who underwent RARP for high-risk disease as determined by D'Amico classification (Gleason 8- 10, stage ≥T2c, and or PSA≥20). Perioperative data was evaluated from a prospectively maintained RARP database. Treatment was considered a failure with PSA levels ≥0.2. RESULTS In total, 363 patients were identified that met high-risk classification. The median age was 63. The median BMI was 29.24. Follow-up ranged from 3 to 98 months. 1-year biochemical recurrence free survival (1-RFS) was 81.2%. 2- year biochemical recurrence free survival (2-RFS) was 63.3%. Gleason score of 8-10 was the most common pre- operative high-risk identifier (66%). Positive surgical margins occurred in 32.8% of patients. Lymph node dissection was performed on 351 patients (97%). The 12 patients that did not receive a lymph node dissection had surgery. In total, 19 patients (5.4%) were found to have positive lymph node involvement. CONCLUSIONS We present our data for the treatment of high-risk prostate cancer with RARP. Consistent with recent, but limited data, RARP appears to be an effective initial treatment for high-risk prostate cancer. Further follow-up for these patients remains necessary to help better understand long-term outcomes following RARP for high-risk prostate cancer. Preoperative Patient Data High Risk Patients (n) 363 Gleason: 6 82 7 42 8 183 9 50 10 6 Clinical Stage: T1C 221 T2A 53 T2B 3 T2C 71 T3A 11 T3B 2 PSA Median (range) 6.06 (0.65-80) N>20 PSA 68 Postoperative Patient Data Gleason: 6 38 7 215 8 72 9 36 10 2 Pathologic Stage T2A 8 T2B 4 T2C 181 T3A 88 T3B 79 T4 3 % Surgical Margins 32.78% % Extracapsular Extension 40.5% Estimated Blood Loss (ml) 112 © 2015 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 193Issue 4SApril 2015Page: e780-e781 Advertisement Copyright & Permissions© 2015 by American Urological Association Education and Research, Inc.MetricsAuthor Information Benjamin Katz More articles by this author Sue-Jean Yu More articles by this author Andrew Lightfoot More articles by this author Giovanni Greaves More articles by this author Elton Llukani More articles by this author Alice McGill More articles by this author Kelly Monahan More articles by this author David Lee 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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,130 | 0,031 |
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 ».