Towards optimal decision making in personalized medicine: Potential value assessment of biomarkers in heart failure exemplars

Treatment selection based on average effects observed in entire target population masks variation among patients (heterogeneity) and may result in less than optimal decision making. Personalized medicine is a new and complex concept, which aims to improve health by offering more tailored and individualized care to patients. Until recently, it was still rather difficult to foresee a broad clinical application of the medical technologies developed to enable personalized medicine. This is mainly because a well-developed methodological framework was still lacking to support the translation of such technologies from bench via bedside and ultimately to society. To this end, this thesis introduced a coherent set of methodologies to investigate the added value for personalized medicine, towards optimal therapeutic and policy decision making. The thesis focused on assessing the clinical impact and commercial potential of biomarker-based strategies using several case studies in heart failure.