Technologies such as decision support systems are expected to help clinicians implement clinical practice guidelines (CPGs) with the aim of decreasing practice variations and improving clinical outcomes. However, if CPGs provide recommendations to improve patient care, they may fail to take into account actual clinical outcomes associated to the recommended treatment, such as adverse events or secondary effects. In this paper, we present a novel experience-based decision support approach applied to the management of breast cancer, the most commonly diagnosed cancer among women worldwide. Capitalizing on the clinical know-how of physicians and the modeling of patient's outcomes and toxicities in a computer interpretable way, we are able to discover new knowledge that helps improving patient-centered clinical care. This work is conducted within the EU Horizon 2020 project DESIREE.