You have accessJournal of UrologyCME1 Apr 2023PD27-11 COMPARISON OF PROSTATE BIOPSY GRADE OBTAINED BY HUMAN PATHOLOGISTS VERSUS AN ARTIFICIAL INTELLIGENCE ALGORITHM FOR PREDICTING BIOCHEMICAL RECURRENCE AFTER RADICAL PROSTATECTOMY Claire de la Calle, Thiago Vidotto, Eric Erak, Daniela Salles, Oluwademilade Dairo, Christian Pavlovich, Misop Han, Joonyoung Cho, In Hye Suh, Hye Yoon Chang, Sun Woo Kim, Michael Gorin, and Tamara Lotan Claire de la CalleClaire de la Calle More articles by this author , Thiago VidottoThiago Vidotto More articles by this author , Eric ErakEric Erak More articles by this author , Daniela SallesDaniela Salles More articles by this author , Oluwademilade DairoOluwademilade Dairo More articles by this author , Christian PavlovichChristian Pavlovich More articles by this author , Misop HanMisop Han More articles by this author , Joonyoung ChoJoonyoung Cho More articles by this author , In Hye SuhIn Hye Suh More articles by this author , Hye Yoon ChangHye Yoon Chang More articles by this author , Sun Woo KimSun Woo Kim More articles by this author , Michael GorinMichael Gorin More articles by this author , and Tamara LotanTamara Lotan More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003305.11AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Several artificial intelligence (AI) algorithms have been developed to streamline biopsy Gleason grading, but most have not been challenged with predicting oncologic outcomes. In this study, we leveraged a cohort of patients with biopsy-detected Grade Group (GG) 2 prostate cancer (PCa) and examined the association of biopsy grade by contemporary pathologist consensus grade or AI algorithm with time to biochemical recurrence (BCR) after radical prostatectomy (RP). METHODS: We identified 286 patients originally diagnosed with GG2 PCa on biopsy who underwent RP at our institution from 2000 to 2014. All biopsies were re-graded by two expert genitourinary pathologists (pathologist 1 and 2). For cases with discrepant reads, a third expert genitourinary pathologist determined the consensus pathology read. GG was also obtained using a previously validated and published AI algorithm. Concordance between pathologist and AI GG was quantified using the quadratic kappa. BCR was defined as two consecutive PSAs ≥0.2 ng/mL. Kaplan-Meier BCR free survival estimates by GG were compared using the log-rank test. RESULTS: After RP median follow-up was 4 years (range 1-14). To date, 16% of the men have had BCR and median time to BCR was 2 years (range 1-10). Biopsy grading between pathologist 1 and 2 generated a kappa of 0.17. Grading between the consensus pathology read and the AI algorithm generated a kappa of 0.33. Grading by consensus pathology read was associated with time to BCR-free survival (log-rank p=0.003) as was the grading by the AI algorithm (log-rank p=0.004; Figure 1). CONCLUSIONS: The AI algorithm Gleason grading demonstrated poor agreement with the consensus contemporary pathology read, but the agreement was also poor between the two pathologists. Yet, our cohort was only comprised of men originally diagnosed with GG2 PCa, a GG usually associated with poor inter-pathologist agreement. Remarkably, both the consensus pathology and the AI algorithm grades on the biopsy stratified patients well for subsequent BCR after RP, suggesting that AI algorithms could be developed to stratify for oncologic outcomes instead of attempting to replicate somewhat subjective human grading. Source of Funding: Research funding from Deep Bio © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e746 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Claire de la Calle More articles by this author Thiago Vidotto More articles by this author Eric Erak More articles by this author Daniela Salles More articles by this author Oluwademilade Dairo More articles by this author Christian Pavlovich More articles by this author Misop Han More articles by this author Joonyoung Cho More articles by this author In Hye Suh More articles by this author Hye Yoon Chang More articles by this author Sun Woo Kim More articles by this author Michael Gorin More articles by this author Tamara Lotan More articles by this author Expand All Advertisement PDF downloadLoading ...