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
Bibliographic record
Abstract
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 ...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.248 | 0.046 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".