To address such PSA test limitations, researchers have incorporated other measurable factors into approaches for the early detection of PCa; these ‘risk assessment tools’ are based on statistical models designed to improve the accuracy and performance of the PSA test.19–22 Logistic regression and artificial neural network (ANN) models are now considered to be the most common and effective statistical techniques in aiding the development of new models to enhance early PCa diagnosis.23 These PCa risk prediction models can be used to aid the testing of men for further investigations. The gene discussed is KLK3; the disease is posterior cortical atrophy.