A multivariate model combining multiparametric MRI, PSA density, and STEAP1-EV density significantly improves prediction of clinically significant prostate cancer (csPCa), achieving an AUC as high as 0.90 (Logozzi et al., 2017). The gene discussed is KLK3; the disease is prostate carcinoma.