  While the 10-year survival rate for localized prostate cancer patients is
very good (>98%), side effects of treatment may limit quality of life
significantly. Erectile dysfunction (ED) is a common burden associated with
increasing age as well as prostate cancer treatment. Although many studies have
investigated the factors affecting erectile dysfunction (ED) after prostate
cancer treatment, only limited studies have investigated whether ED can be
predicted before the start of treatment. The advent of machine learning (ML)
based prediction tools in oncology offers a promising approach to improve
accuracy of prediction and quality of care. Predicting ED may help aid shared
decision making by making the advantages and disadvantages of certain
treatments clear, so that a tailored treatment for an individual patient can be
chosen. This study aimed to predict ED at 1-year and 2-year post-diagnosis
based on patient demographics, clinical data and patient-reported outcomes
(PROMs) measured at diagnosis.
