Different nomograms exist for the preoperative prediction of pelvic lymph-node metastatic disease in individual patients with prostate cancer (PCa). These nomograms do not incorporate modern imaging techniques such as prostate-specific membrane antigen (PSMA) positron emission tomography (PET).
To determine the predictive performance of the Briganti 2017, Memorial Sloan Kettering Cancer Center (MSKCC), and Briganti 2019 nomograms with the addition of PSMA-PET in an international, multicenter, present-day cohort of patients undergoing robot-assisted radical prostatectomy (RARP) and extended pelvic lymph-node dissection (ePLND) for localized PCa.
All 757 eligible patients who underwent a PSMA-PET prior to RARP and ePLND in three reference centers for PCa surgery between January 2016 and November 2020 were included.
Performance of the three nomograms was assessed using the receiver operating characteristic curve-derived area under the curve (AUC), calibration plots, and decision curve analyses. Subsequently, recalibration and addition of PSMA-PET to the nomograms were performed.
Overall, 186/757 patients (25%) had pelvic lymph-node metastatic (pN1) disease on histopathological examination. AUCs of the Briganti 2017, MSKCC, and Briganti 2019 nomograms were 0.70 (95% confidence interval [95% CI]: 0.64-0.77), 0.71 (95% CI: 0.65-0.77), and 0.76 (95% CI: 0.71-0.82), respectively. PSMA-PET findings showed a significant association with pN1 disease when added to the nomograms (p < 0.001). Addition of PSMA-PET substantially improved the discriminative ability of the models yielding cross-validated AUCs of 0.76 (95% CI: 0.70-0.82), 0.77 (95% CI: 0.72-0.83), and 0.82 (95% CI: 0.76-0.87), respectively. In decision curve analyses, the addition of PSMA-PET to the three nomograms resulted in increased net benefits.
The addition of PSMA-PET to the previously developed nomograms showed substantially improved predictive performance, which suggests that PSMA-PET is a likely future candidate for a modern predictive nomogram.
Different tools have been developed to individualize the prediction of prostate cancer spread to lymph nodes before surgery. We found that the inclusion of modern imaging (prostate-specific membrane antigen positron emission tomography) improved substantially the overall performance of these prediction tools.
European urology. 2021 May 20 [Epub ahead of print]
Dennie Meijer, Pim J van Leeuwen, Matthew J Roberts, Amila R Siriwardana, Andrew Morton, John W Yaxley, Hemamali Samaratunga, Louise Emmett, Peter M van de Ven, Henk G van der Poel, Maarten L Donswijk, Thierry N Boellaard, Ivo G Schoots, Daniela E Oprea-Lager, Geoffrey D Coughlin, André N Vis
Department of Urology, Prostate Cancer Network Netherlands, Amsterdam University Medical Center, VU University, Amsterdam, The Netherlands; Department of Radiology & Nuclear Medicine, Cancer Center Amsterdam, Amsterdam University Medical Center, VU University, Amsterdam, The Netherlands. Electronic address: ., Department of Urology, Prostate Cancer Network Netherlands, The Netherlands Cancer Institute, Amsterdam, The Netherlands., Department of Urology, Royal Brisbane and Women's Hospital, Brisbane, Australia; University of Queensland Centre for Clinical Research, Herston, Australia; Department of Urology, Redcliffe Hospital, Brisbane, Australia., Department of Urology, Royal Brisbane and Women's Hospital, Brisbane, Australia., Department of Urology, Royal Brisbane and Women's Hospital, Brisbane, Australia; Faculty of Medicine, University of Queensland, Brisbane, Australia., Department of Urology, Royal Brisbane and Women's Hospital, Brisbane, Australia; Faculty of Medicine, University of Queensland, Brisbane, Australia; Department of Urology, Wesley Hospital, Brisbane, Australia., Faculty of Medicine, University of Queensland, Brisbane, Australia; Department of Pathology, Aquesta Uropathology, Brisbane, Australia., St. Vincent's Clinical School, University of New South Wales, Kensington, Australia; Department of Theranostics and Nuclear Medicine, St. Vincent's Hospital Sydney, Darlinghurst, Australia., Department of Epidemiology and Data Science, Amsterdam University Medical Center, VU University, Amsterdam, The Netherlands., Department of Nuclear Medicine, The Netherlands Cancer Institute, Amsterdam, The Netherlands., Department of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands., Department of Radiology & Nuclear Medicine, Cancer Center Amsterdam, Amsterdam University Medical Center, VU University, Amsterdam, The Netherlands., Faculty of Medicine, University of Queensland, Brisbane, Australia; Department of Urology, Wesley Hospital, Brisbane, Australia., Department of Urology, Prostate Cancer Network Netherlands, Amsterdam University Medical Center, VU University, Amsterdam, The Netherlands; Department of Urology, Prostate Cancer Network Netherlands, The Netherlands Cancer Institute, Amsterdam, The Netherlands.