Timo Soeterik

140 CHAPTER 8 ABSTRACT Background : Two established prediction tools that can be used to assess the probability of pelvic lymph node involvement (LNI) in patients with primary prostate cancer are the Memorial Sloan Kettering Cancer Centre (MSKCC; 2018) and Briganti (2012) nomograms. However, these nomograms include DRE-based clinical tumour stage (T-stage) as impute parameter. It is unclear if using T-stage assessed by multiparametric magnetic resonance imaging (mpMRI) improves predictive performance. Therefore, the aim of this study is to assess the impact of mpMRI T-stage on the model performance of two well-established nomograms for the prediction of LNI. Methods : Patients undergoing robot-assisted extended pelvic lymph node dissection (ePLND) from 2015 to 2019 at three teaching hospitals were retrospectively evaluated. Risk of pelvic LNI was calculated four times for each patient, using T-stage assessed by digital rectal examination (DRE) and by mpMRI, in the MSKCC (2018) and Briganti (2012) nomograms. Discrimination (area under the curve [AUC]), calibration, and net benefit of these four strategies were assessed and compared. Results : A total of 1062 patients were included, of whom 301 (28%) had histologically proven LNI. Using DRE T-stage resulted in AUCs of 0.71 (95% CI 0.70 - 0.72) for the MSKCC and 0.73 (95% CI 0.72 – 0.74) for the Briganti nomogram. Using mpMRI T-stage, the AUCs were 0.72 (95% CI 0.71 – 0.73) for the MSKCC and 0.75 (95% CI 0.74 – 0.76) for the Briganti nomogram. The mpMRI T-stage resulted in equivalent calibration compared with DRE T-stage. Combined use of mpMRI T-stage and the Briganti 2012 nomogram was shown to be superior in terms of AUC, calibration, and net benefit. Use of mpMRI T-stage led to increased sensitivity for the detection of LNI for all risk thresholds in both models, countered by a decreased specificity, compared with DRE T-stage. Conclusions : Clinical T-stage assessed by mpMRI is an appropriate alternative for T-stage assessed by DRE to determine nomogram-based risk of LNI in patients with prostate cancer, and was associated with improved model performance of both the MSKCC 2018 and Briganti 2012 nomograms.