Mp19-16 Incorporating Prostate Mri Imaging Characteristics to Improve Prostate Cancer Diagnosis and Risk Stratification: An Analysis and Nomogram Derived From a 9,536 Patient, Multi-Institutional Cohort

You have accessJournal of UrologyProstate Cancer: Detection & Screening I (MP19)1 May 2024MP19-16 INCORPORATING PROSTATE MRI IMAGING CHARACTERISTICS TO IMPROVE PROSTATE CANCER DIAGNOSIS AND RISK STRATIFICATION: AN ANALYSIS AND NOMOGRAM DERIVED FROM A 9,536 PATIENT, MULTI-INSTITUTIONAL COHORT Luke A. R. Shumaker, Andrew Fang, Masatomo Kaneko, Lorenzo Ramacciotti, Nachiketh Prakash, Arighno Das, Hiten Patel, Ghazal Khajir, Richard Fan, Shu Wang, Kevin Pineault, Abhinav Sidana, Gopal Gupta, Christopher Filson, James Wysock, M. Minhaj Siddiqui, Geoffrey A. Sonn, Preston Sprenkle, Ashley Ross, David Jarrard, Sanoj Punnen, Andre Abreu, and Soroush Rais-Bahrami Luke A. R. ShumakerLuke A. R. Shumaker , Andrew FangAndrew Fang , Masatomo KanekoMasatomo Kaneko , Lorenzo RamacciottiLorenzo Ramacciotti , Nachiketh PrakashNachiketh Prakash , Arighno DasArighno Das , Hiten PatelHiten Patel , Ghazal KhajirGhazal Khajir , Richard FanRichard Fan , Shu WangShu Wang , Kevin PineaultKevin Pineault , Abhinav SidanaAbhinav Sidana , Gopal GuptaGopal Gupta , Christopher FilsonChristopher Filson , James WysockJames Wysock , M. Minhaj SiddiquiM. Minhaj Siddiqui , Geoffrey A. SonnGeoffrey A. Sonn , Preston SprenklePreston Sprenkle , Ashley RossAshley Ross , David JarrardDavid Jarrard , Sanoj PunnenSanoj Punnen , Andre AbreuAndre Abreu , and Soroush Rais-BahramiSoroush Rais-Bahrami View All Author Informationhttps://doi.org/10.1097/01.JU.0001008716.22569.77.16AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Prostate cancer risk stratification continues to rely most commonly on PSA levels and digital rectal exam. Despite the steep increase in prostate MRI (PMRI) studies performed and the routine correlation of imaging with location-specific tissue evaluation by MRI-ultrasound fusion, PMRI characteristics remain absent from risk prediction tools. METHODS: We collected PMRI and associated fusion biopsy data from 11 high-volume centers. These centers actively maintain biopsy databases from which the data was retrieved retrospectively. Inclusion criteria for our cohort >= 1 PIRADS 3-5 lesion with accompanying biopsy data. Basic patient factors and prior biopsy history were captured across all institutions. Clinically significant prostate cancer (csPCa) was defined as Gleason score >=2. Data was cleaned, statistical analyses performed, and figures generated using R Version 4.3.4 (R Foundation for Statistical Computing). Multivariable logistic regression modeling was performed on training data from 6 centers with the remaining 5 separated for a testing data set. The prediction profile for eachregression model was compared to the real-world testing cohort to evaluate performance. RESULTS: 9,536 patients met inclusion criteria. ogistic regression demonstrated that highest PIRADS lesion alone meaningfully stratified risk of csPCa (Figure 1). An optimized predictive nomogram, which included variables highest PIRADS lesion, PSA density, and age performed best when predicting csPCa with an AUC of 0.79. Using a decision point at 15% nomogram-predicted risk for csPCa sensitivity was 84% and negative predictive value was 97%. Using this nomogram 12% of post MRI biopsies could be avoided while only missing 1.6 csPCa cases per 100 men. CONCLUSIONS: When PIRADS category is included in a predictive nomogram with other common patient factors, risk of csPCa can be accurately predicted. The predicted risk decision point could be tailored to an individual patient's risk tolerance and be a useful aid in decision making surrounding initial or repeat biopsy. Modern prostate cancer risk tools should make use of PMRI characteristics. Download PPT Source of Funding: None © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e316 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Luke A. R. Shumaker More articles by this author Andrew Fang More articles by this author Masatomo Kaneko More articles by this author Lorenzo Ramacciotti More articles by this author Nachiketh Prakash More articles by this author Arighno Das More articles by this author Hiten Patel More articles by this author Ghazal Khajir More articles by this author Richard Fan More articles by this author Shu Wang More articles by this author Kevin Pineault More articles by this author Abhinav Sidana More articles by this author Gopal Gupta More articles by this author Christopher Filson More articles by this author James Wysock More articles by this author M. Minhaj Siddiqui More articles by this author Geoffrey A. Sonn More articles by this author Preston Sprenkle More articles by this author Ashley Ross More articles by this author David Jarrard More articles by this author Sanoj Punnen More articles by this author Andre Abreu More articles by this author Soroush Rais-Bahrami More articles by this author Expand All Advertisement PDF downloadLoading ...