P2-05 THE NEXT GENERATION TRIAL – ASSESSING <sup>18</sup> F-PSMA-1007 POSITRON EMISSION TOMOGRAPHY AND MAGNETIC RESONANCE IMAGING IN THE PRIMARY STAGING OF PROSTATE CANCER PATIENTS
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Résumé
You have accessJournal of UrologyParadigm-shifting, Practice-changing Clinical Trials in Urology (P2)1 May 2024P2-05 THE NEXT GENERATION TRIAL – ASSESSING 18F-PSMA-1007 POSITRON EMISSION TOMOGRAPHY AND MAGNETIC RESONANCE IMAGING IN THE PRIMARY STAGING OF PROSTATE CANCER PATIENTS Nikhile Mookerji, Tyler Pfanner, Amaris Hui, Guocheng Huang, Patrick Albers, Rohan Mittal, Stacey Broomfield, Lucas Dean, Blair St. Martin, Niels-Erik Jacobsen, Howard Evans, Yuan Gao, Ryan Hung, Jonathan Abele, Peter Dromparis, Joema Felipe Lima, Tarek Bismar, Evangelos Michelakis, Gopinath Sutendra, Frank Wuest, Wendy Tu, Benjamin Adam, Christopher Fung, Alexander Tamm, and Adam Kinnaird Nikhile MookerjiNikhile Mookerji , Tyler PfannerTyler Pfanner , Amaris HuiAmaris Hui , Guocheng HuangGuocheng Huang , Patrick AlbersPatrick Albers , Rohan MittalRohan Mittal , Stacey BroomfieldStacey Broomfield , Lucas DeanLucas Dean , Blair St. MartinBlair St. Martin , Niels-Erik JacobsenNiels-Erik Jacobsen , Howard EvansHoward Evans , Yuan GaoYuan Gao , Ryan HungRyan Hung , Jonathan AbeleJonathan Abele , Peter DromparisPeter Dromparis , Joema Felipe LimaJoema Felipe Lima , Tarek BismarTarek Bismar , Evangelos MichelakisEvangelos Michelakis , Gopinath SutendraGopinath Sutendra , Frank WuestFrank Wuest , Wendy TuWendy Tu , Benjamin AdamBenjamin Adam , Christopher FungChristopher Fung , Alexander TammAlexander Tamm , and Adam KinnairdAdam Kinnaird View All Author Informationhttps://doi.org/10.1097/01.JU.0001015816.87470.c9.05AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Prostate specific membrane antigen (PSMA) is a type II transmembrane protein which demonstrates overexpression in the vast majority of prostate cancers and correlates with the aggressiveness of the tumor. PSMA PET imaging has been shown to be superior to conventional imaging (CT/Bone scan) in the workup of prostate cancer. The objective of this study is to determine the accuracy and role of 18F-PSMA-1007 PET and mpMRI in the primary locoregional staging of intermediate and high-risk prostate cancer. METHODS: The Next Generation Trial (NCT05141760) was a Phase II prospective validating paired-cohort trial assessing 18F-PSMA-1007 PET/CT and mpMRI for locoregional staging of prostate cancer, with final histopathology as the gold standard comparator in 134 patients undergoing prostatectomy. Radiologists, nuclear medicine physicians, and pathologists were blinded to preoperative clinical, pathology, and imaging data. The primary outcome was correct identification of the prostate cancer tumor ('T') stage. The secondary outcomes were correct identification of the dominant nodule, laterality, extracapsular extension, and seminal vesical invasion. RESULTS: PSMA PET was superior to mpMRI for the accurate identification of the final pathological T stage (45% vs. 28%, p=0.003). PSMA PET was also superior to MRI for the correct identification of the dominant nodule (94% vs. 83%, p=0.007), laterality (64% vs. 44%, p=0.001), and extracapsular extension (75% vs. 63%, p=0.014), but not for seminal vesicle invasion (91% vs. 85%, p=0.065). On a per tumor nodule analysis, PSMA PET detected more GGG2 or greater nodules than MRI (86% vs. 62%, p<0.001). CONCLUSIONS: In this trial, 18F-PSMA-1007 PET/CT was superior to mpMRI for the locoregional staging of prostate cancer. These findings support the use of PSMA PET in the preoperative workflow of intermediate- and high-risk tumors. Download PPT Source of Funding: University Hospital Foundation, Bird Dogs for Prostate Cancer Research, Alberta Cancer Foundation, Canadian Urological Association Scholarship Foundation © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5S2May 2024Page: e3 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Nikhile Mookerji More articles by this author Tyler Pfanner More articles by this author Amaris Hui More articles by this author Guocheng Huang More articles by this author Patrick Albers More articles by this author Rohan Mittal More articles by this author Stacey Broomfield More articles by this author Lucas Dean More articles by this author Blair St. Martin More articles by this author Niels-Erik Jacobsen More articles by this author Howard Evans More articles by this author Yuan Gao More articles by this author Ryan Hung More articles by this author Jonathan Abele More articles by this author Peter Dromparis More articles by this author Joema Felipe Lima More articles by this author Tarek Bismar More articles by this author Evangelos Michelakis More articles by this author Gopinath Sutendra More articles by this author Frank Wuest More articles by this author Wendy Tu More articles by this author Benjamin Adam More articles by this author Christopher Fung More articles by this author Alexander Tamm More articles by this author Adam Kinnaird 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 | 0,007 | 0,016 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,003 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,004 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,004 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,248 | 0,046 |
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 ».