Abstract
e17667 Background: Improved Early Stage Breast Cancer (ESBC) screening, subtype classification and treatment lead to increased clinical complexity. Risk prediction models (RPM), such as Adjuvant! Online (AO), have been created to help oncologists to select ESBC patients who might benefit from adjuvant therapy. Evaluating clinical relevance of AO is necessary to provide patients with the best treatment. The objective of the study is to determine, first, how AO clinical relevance is currently assessed; secondly, if there might be other ethically relevant evaluation criteria. Methods: First, we analyzed the literature dealing with AO to assess the most common evaluation methods of its clinical relevance. We determined the arguments underlying AO use guidelines. Secondly, we compared AO-based medical decision process to Evidence-Based Medicine (EBM) decision-making characteristics. We determined the changes induced by AO use on the medical decision reference process. We described the inherent and specific cha...
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