Is there a role for pure clinical prediction models in prostate cancer in the contemporary era?

The identification of men with localised prostate cancer at higher risk of adverse pathological outcomes after radical prostatectomy (RP) would assist physicians in preoperative patient counselling and in tailoring the most appropriate treatment strategy. In this issue of the BJUI, Tosoian et al. [1] have updated the Partin Tables in contemporary patients with localised prostate cancer. The authors should be commended for undertaking a wellperformed study evaluating a large cohort of patients treated at a high-volume centre. Notably, they were able to show that the Partin Tables still represent an accurate tool for identifying men at higher risk of adverse pathological features [1]. Having said this, the first question we should ask ourselves is whether preoperative models based on clinical variables only still play a role in contemporary patients. The Partin Tables were developed in 1993 and since then they have undergone a series of updates, all of which are based on virtually the same variables included in the original analyses [1]. However, recent implementations, including biomarkers and imaging, have been introduced to better stage prostate cancer. These novel approaches are usually added to clinical variables to improve patient risk stratification. Multi-parametric MRI (mp-MRI) represents the major game changer in this setting, being now recommended for prostate cancer staging in all men with high-risk disease and in those with less favourable intermediate-risk prostate cancer [2]. In the era of modern and sophisticated approaches, are models using clinical variables only still clinically valuable? To answer this question, we can consider two major settings, namely nodal and local staging.