T Stonier1,2, A L Tin3, D D Sjoberg3, G Jibara1, A J Vickers3, S Fine1, J Eastham1. 1. Department of Surgery (Urology Service), Memorial Sloan Kettering Cancer Center, New York, New York. 2. St George's Hospital, London, UK. 3. Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York.
Abstract
PURPOSE: The National Comprehensive Cancer Network® recommends that selected men with grade group 2 prostate cancer be considered for active surveillance. However, selecting which patients with grade group 2 disease can be safely managed by active surveillance remains controversial. The aim of this study was to evaluate the association of multiparametric magnetic resonance imaging with adverse pathology in the radical prostatectomy specimen of men with favorable risk grade group 2 prostate cancer, which could help select patients for active surveillance. MATERIALS AND METHODS: We retrospectively analyzed a cohort of patients with favorable grade group 2 disease who underwent radical prostatectomy between 2010 and 2019. Preoperative multiparametric magnetic resonance imaging was scored as negative (no identifiable lesion), positive (identifiable lesion) or equivocal. We defined a multivariable logistic regression model with multiparametric magnetic resonance imaging score as the predictor and adverse pathology (up staging to T3a/b disease, upgrading to ≥grade group 3 or lymph node invasion) as the outcome, adjusting for preoperative prostate specific antigen, biopsy Gleason grade, clinical stage, and number of negative and positive prostate biopsy cores. Secondary outcomes of biochemical recurrence, grade group upgrading alone and the added value of incorporating multiparametric magnetic resonance imaging data into the nomogram were also investigated. RESULTS: We identified 1,117 patients with favorable risk grade group 2 disease who underwent radical prostatectomy. Positive multiparametric magnetic resonance imaging was associated with higher rates of adverse pathology (OR 2.55, 95% CI 1.75-3.40, p <0.0001) and upgrading (OR 3.89, 95% CI 2.00-7.56, p <0.0001). However, as our study included only grade group 2 patients who underwent radical prostatectomy, our cohort may represent a higher risk group than grade group 2 patients as a whole. Adding multiparametric magnetic resonance imaging results to a standard prediction model led to higher net benefit on decision curve analysis. An identifiable lesion on multiparametric magnetic resonance imaging was associated with an increased risk of aggressive pathological features in the radical prostatectomy specimen of patients with favorable risk grade group 2 prostate cancer who were potential active surveillance candidates. This information could be used to inform biopsy strategy, counsel patients on treatment options and guide strategies for those on active surveillance. CONCLUSIONS: Combining multiple magnetic resonance imaging modalities (multiparametric magnetic resonance imaging) provides a more accurate prediction of the risk presented by prostate cancer than current prediction methods. In this study, positive magnetic resonance imaging results approximately doubled the chances that a patient with favorable risk prostate cancer would be found to have adverse pathology when their prostate was removed. Thus, multiparametric magnetic resonance imaging could help select patients with favorable risk cancer who may be good candidates for active surveillance, and help guide biopsy and surveillance strategies for such patients.
PURPOSE: The National Comprehensive Cancer Network® recommends that selected men with grade group 2 prostate cancer be considered for active surveillance. However, selecting which patients with grade group 2 disease can be safely managed by active surveillance remains controversial. The aim of this study was to evaluate the association of multiparametric magnetic resonance imaging with adverse pathology in the radical prostatectomy specimen of men with favorable risk grade group 2 prostate cancer, which could help select patients for active surveillance. MATERIALS AND METHODS: We retrospectively analyzed a cohort of patients with favorable grade group 2 disease who underwent radical prostatectomy between 2010 and 2019. Preoperative multiparametric magnetic resonance imaging was scored as negative (no identifiable lesion), positive (identifiable lesion) or equivocal. We defined a multivariable logistic regression model with multiparametric magnetic resonance imaging score as the predictor and adverse pathology (up staging to T3a/b disease, upgrading to ≥grade group 3 or lymph node invasion) as the outcome, adjusting for preoperative prostate specific antigen, biopsy Gleason grade, clinical stage, and number of negative and positive prostate biopsy cores. Secondary outcomes of biochemical recurrence, grade group upgrading alone and the added value of incorporating multiparametric magnetic resonance imaging data into the nomogram were also investigated. RESULTS: We identified 1,117 patients with favorable risk grade group 2 disease who underwent radical prostatectomy. Positive multiparametric magnetic resonance imaging was associated with higher rates of adverse pathology (OR 2.55, 95% CI 1.75-3.40, p <0.0001) and upgrading (OR 3.89, 95% CI 2.00-7.56, p <0.0001). However, as our study included only grade group 2 patients who underwent radical prostatectomy, our cohort may represent a higher risk group than grade group 2 patients as a whole. Adding multiparametric magnetic resonance imaging results to a standard prediction model led to higher net benefit on decision curve analysis. An identifiable lesion on multiparametric magnetic resonance imaging was associated with an increased risk of aggressive pathological features in the radical prostatectomy specimen of patients with favorable risk grade group 2 prostate cancer who were potential active surveillance candidates. This information could be used to inform biopsy strategy, counsel patients on treatment options and guide strategies for those on active surveillance. CONCLUSIONS: Combining multiple magnetic resonance imaging modalities (multiparametric magnetic resonance imaging) provides a more accurate prediction of the risk presented by prostate cancer than current prediction methods. In this study, positive magnetic resonance imaging results approximately doubled the chances that a patient with favorable risk prostate cancer would be found to have adverse pathology when their prostate was removed. Thus, multiparametric magnetic resonance imaging could help select patients with favorable risk cancer who may be good candidates for active surveillance, and help guide biopsy and surveillance strategies for such patients.
Entities:
Keywords:
magnetic resonance imaging; prognosis; prostatic neoplasms; watchful waiting
Authors: James L Mohler; Emmanuel S Antonarakis; Andrew J Armstrong; Anthony V D'Amico; Brian J Davis; Tanya Dorff; James A Eastham; Charles A Enke; Thomas A Farrington; Celestia S Higano; Eric Mark Horwitz; Michael Hurwitz; Joseph E Ippolito; Christopher J Kane; Michael R Kuettel; Joshua M Lang; Jesse McKenney; George Netto; David F Penson; Elizabeth R Plimack; Julio M Pow-Sang; Thomas J Pugh; Sylvia Richey; Mack Roach; Stan Rosenfeld; Edward Schaeffer; Ahmad Shabsigh; Eric J Small; Daniel E Spratt; Sandy Srinivas; Jonathan Tward; Dorothy A Shead; Deborah A Freedman-Cass Journal: J Natl Compr Canc Netw Date: 2019-05-01 Impact factor: 11.908
Authors: Izak Faiena; Amirali Salmasi; Neil Mendhiratta; Daniela Markovic; Preeti Ahuja; William Hsu; David A Elashoff; Steven S Raman; Robert E Reiter Journal: J Urol Date: 2019-01 Impact factor: 7.450
Authors: Doo Yong Chung; Min Seok Kim; Jong Soo Lee; Hyeok Jun Goh; Dong Hoon Koh; Won Sik Jang; Chang Hee Hong; Young Deuk Choi Journal: J Clin Med Date: 2019-04-19 Impact factor: 4.241
Authors: Vasilis Stavrinides; Francesco Giganti; Bruce Trock; Shonit Punwani; Clare Allen; Alex Kirkham; Alex Freeman; Aiman Haider; Rhys Ball; Neil McCartan; Hayley Whitaker; Clement Orczyk; Mark Emberton; Caroline M Moore Journal: Eur Urol Date: 2020-04-30 Impact factor: 20.096