MP64-05 A NEW MODEL FOR PREDICTION OF HIGH-RISK FEATURES AMONG UNFAVORABLE INTERMEDIATE RISK PROSTATE CANCER PATIENTS

Abstract

You have accessJournal of UrologyProstate Cancer: Localized: Surgical Therapy VI (MP64)1 Sep 2021MP64-05 A NEW MODEL FOR PREDICTION OF HIGH-RISK FEATURES AMONG UNFAVORABLE INTERMEDIATE RISK PROSTATE CANCER PATIENTS Lara Franziska Stolzenbach, Luigi Nocera, Claudia Collà-Ruvolo, Mike Wenzel, Zhe Tian, Alberto Briganti, Sophie Knipper, Tobias Maurer, Derya Tilki, Hartwig Huland, Markus Graefen, and Pierre I. Karakiewicz Lara Franziska StolzenbachLara Franziska Stolzenbach More articles by this author , Luigi NoceraLuigi Nocera More articles by this author , Claudia Collà-RuvoloClaudia Collà-Ruvolo More articles by this author , Mike WenzelMike Wenzel More articles by this author , Zhe TianZhe Tian More articles by this author , Alberto BrigantiAlberto Briganti More articles by this author , Sophie KnipperSophie Knipper More articles by this author , Tobias MaurerTobias Maurer More articles by this author , Derya TilkiDerya Tilki More articles by this author , Hartwig HulandHartwig Huland More articles by this author , Markus GraefenMarkus Graefen More articles by this author , and Pierre I. KarakiewiczPierre I. Karakiewicz More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002104.05AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Under current guidelines, radical prostatectomies (RP) for unfavorable intermediate risk prostate cancer (UIR PCa) patients are deferred . However, high risk criteria (pT3-4/pN1 stage and/or GGG IV-V) will be present in some unfavorable intermediate risk prostate cancer (UIR PCa) patients. These individuals should be prioritized for definitive therapy. We attempted to identify them. METHODS: A total of 2,024 UIR PCa patients treated with radical prostatectomy were abstracted from an institutional database (2000-2018). Multivariable logistic regression models predicting high risk criteria (pT3-4/pN1 stage and/or GGG IV-V) in IR PCa were developed, validated and directly compared with NCCN IR PCa stratification. RESULTS: All 2,024 patients were randomly divided between development (n=1,012, 50.0%) and validation cohorts (n=1,012, 50.0%). The development cohort was used to fit a new model (PSA level, clinical T stage, biopsy Gleason Grade Group (GGG), cumulative tumor length in available biopsy cores [all p<0.001]) to predict high-risk criteria according to RP pathology, using. At RP, the rates of pT3-4/pN1, GGG IV-V and of both were 52.2, 3.7 and 55.9%, respectively. Within the validation cohort, the new model outperformed any combination of NCCN UIR PCa criteria in accuracy (70.1 vs 63.0%), calibration and decision curve analyses. The new model derived probability cutoff of 50.0% for presence of pT3-4/pN1/GGG IV-V identified 317 (31.1%) of 1,012 patients, in whom the rate of pT3-4/pN1/GGG IV-V was 65.9%, instead of average 44.6%. CONCLUSIONS: We developed a new model that can accurately identify a subset of NCCN UIR PCa patients with significantly higher proportion of high-risk criteria (pT3-4/pN1 stage and/or GGG IV-V). These individuals should be prioritized for definitive therapy during COVID-19-pandemic. Source of Funding: There was no external financial support for this study. The authors declare that they have no conflict of interest © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e1111-e1111 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information Lara Franziska Stolzenbach More articles by this author Luigi Nocera More articles by this author Claudia Collà-Ruvolo More articles by this author Mike Wenzel More articles by this author Zhe Tian More articles by this author Alberto Briganti More articles by this author Sophie Knipper More articles by this author Tobias Maurer More articles by this author Derya Tilki More articles by this author Hartwig Huland More articles by this author Markus Graefen More articles by this author Pierre I. Karakiewicz More articles by this author Expand All Advertisement Loading ...