Comparison of multiparametric prostate MRI (mpMRI) vs. positive biopsy cores on risk of adverse pathologic outcomes after radical prostatectomy (RP) in Gleason grade group (GG) 2 prostate cancer.

S Sam Kwon (George Washington University School of Medicine and Health Sciences, Washington, DC) V Vincent Eric Xu (George Washington University School of Medicine and Health Sciences, Washington, DC) R Rollins Turner (George Washington University School of Medicine and Health Sciences, Washington, DC) M Mateo Ugarte (George Washington University School of Medicine and Health Sciences, Washington, DC) J Joseph Manus (George Washington University School of Medicine and Health Sciences, Washington, DC) D Diego Gonzalez K Kris Kokoneshi (George Washington University School of Medicine and Health Sciences, Washington, DC) R Rachel Bernardo (George Washington University School of Medicine and Health Sciences, Washington, DC) M Michael Joseph Whalen (George Washington University School of Medicine and Health Sciences, Washington, DC)

Abstract

320 Background: Current guidelines endorse prognostication with percentage of positive biopsy cores when deciding upon definitive treatment in intermediate risk prostate cancer. However, in the era of mpMRI, we hypothesize that Prostate Imaging Reporting and Data System (PI-RADS) scoring is more informative for predicting adverse pathologic outcomes after RP. Methods: A retrospective study was conducted of patients with GG 2 prostate cancer from a single institution who underwent RP from 2016-2025. Patients were included based on preoperative metrics, including percentage of positive biopsy cores (≥50% or <50%), mpMRI maximum lesion diameter (<15 mm or ≥15 mm), and PI-RADS score (<4 or ≥4). Multivariable logistic regression analyses identified significant predictors of postoperative upgrading and upstaging. Results: A total of 87 patients were included with a median preoperative PSA value of 7 ng/mL (IQR 5.65–9.90) and prostate volume of 59.14 mL (IQR 38.5–81.00). Of 87 patients, 41.4% were White and 41.4% were Black. In multivariable analysis including preoperative PSA value and prostate volume, high positive biopsy cores and high mpMRI lesion diameter were not associated with pathological upgrading, upstaging and adverse pathology. However, high PI-RADS score was independently associated with pathological upstaging (p = 0.02) and adverse pathology, including pT3-4 or pN1+ (p = 0.011). Conclusions: More accurate risk stratification is needed to guide treatment decisions for intermediate risk prostate cancer. Our findings highlight greater PI-RADS score as a predictive marker of adverse pathologic features at RP. While our analysis was limited by small cohort size, our results showed no significant association between percentage of positive biopsy cores and adverse pathologic findings. Therefore, consideration of mpMRI in future optimization of existing NCCN risk stratifications may be warranted. Future investigation is needed to confirm these findings. Multivariable logistic regression model for predicting postoperative pathological upgrading, pathological upstaging (pT3-4), and adverse pathology (pT3-4 or pN1+). Pathological Upgrading (GG ≥ 3) Pathological Upstaging(pT3-4) Adverse Pathology(pT3-4 or pN1+) Variables OR (95% CI) P OR (95% CI) P OR (95% CI) P Preoperative PSA 1.01 (0.89-1.25) 0.54 0.94 (0.82-1.08) 0.39 0.94 (0.81-1.08) 0.36 Prostate volume 1.00 (0.98-1.01) 0.66 1.00 (0.98-1.01) 0.47 0.99 (0.98-1.01) 0.39 Positive Biopsy Cores ≥ 50% 1.01 (0.44-2.31) 0.98 1.21 (0.66-2.24) 0.54 1.33 (0.71-2.48) 0.37 Max Lesion Diameter ≥ 15mm 1.01 (0.92-1.1) 0.91 1.00 (0.93-1.07) 0.89 0.99 (0.93-1.06) 0.85 PI-RADS ≥ 4 1.16 (0.47-2.88) 0.75 2.36 (1.15-4.83) 0.02 2.6 (1.25-5.42) 0.011

Article Details

Volume / Issue Vol. 44, Issue 7_suppl
Published March 01, 2026
Pages 320-320
ISSN 0732-183X
Publisher Lippincott Williams & Wilkins

Journal Info

Journal of Clinical Oncology

Lippincott Williams & Wilkins

ISSN: 0732-183X Health Sciences

Authors (9)

S

Sam Kwon

George Washington University School of Medicine and Health Sciences, Washington, DC

V

Vincent Eric Xu

George Washington University School of Medicine and Health Sciences, Washington, DC

R

Rollins Turner

George Washington University School of Medicine and Health Sciences, Washington, DC

M

Mateo Ugarte

George Washington University School of Medicine and Health Sciences, Washington, DC

J

Joseph Manus

George Washington University School of Medicine and Health Sciences, Washington, DC

D

Diego Gonzalez

K

Kris Kokoneshi

George Washington University School of Medicine and Health Sciences, Washington, DC

R

Rachel Bernardo

George Washington University School of Medicine and Health Sciences, Washington, DC

M

Michael Joseph Whalen

George Washington University School of Medicine and Health Sciences, Washington, DC