The nomogram reported by Gandaglia et al (The key combined value of multiparametric magnetic resonance imaging, and magnetic resonance imaging-targeted and concomitant systematic biopsies for the prediction of adverse pathological features in prostate cancer patients undergoing radical prostatectomy. Eur Urol 2020;77:733-41) predicting extracapsular extension (ECE) or seminal vesicle invasion (SVI) has been developed using multiparametric magnetic resonance imaging (MRI) parameters and MRI-targeted biopsy. We aimed to validate this nomogram externally by analyzing 566 patients harboring prostate cancer diagnosed on MRI-targeted biopsy followed by radical prostatectomy. At final pathology, 37% and 12% patients had ECE and SVI, respectively. Performance of the nomogram, in comparison with the Memorial Sloan Kettering Cancer Center (MSKCC) model and Partin tables, was evaluated using discrimination, calibration, and decision curve analysis. Regarding ECE prediction, the nomogram showed higher discrimination (71.8% vs 69.8%, p = 0.3 and 71.8% vs 61.3%, p < 0.001), and similar miscalibration and net benefit for probability threshold above 30% when compared with MSKCC model and Partin tables, respectively. Performance of the nomogram with regard to SVI was comparable in terms of discrimination (68.5% vs 70.4% vs 67.8%, p ≥ 0.6), presenting a slight overestimation on calibration plots and a net benefit for probability threshold above 7.5%. This is the first multicentric study that externally validates a nomogram predicting ECE and SVI in patients diagnosed with MRI-targeted biopsy. Its performance was less optimistic than expected, and implementation of MRI in this setting was not associated with a clear improvement in patient selection and clinical usefulness when compared with available models. We proposed an updated version of the nomogram predicting ECE using the recalibration method, which leads to an improvement in its performance and needs to be validated in another external set. PATIENT SUMMARY: We validate a prediction tool based on multiparametric magnetic resonance imaging (MRI) parameters and MRI-targeted biopsy predicting extracapsular extension and seminal vesicle invasion at radical prostatectomy. An improvement of patient selection was not clearly demonstrated when compared with available models based on clinical parameters, and implementation of MRI in this setting still needs to be clarified.