A heterogeneous disease such as Parkinson’s disease (PD) demands care that is closely tailored to the needs, preferences, and characteristics of each individual living with this condition. Being able to make treatment choices together with individual persons living with PD based on the individual’s (disease-) characteristics and preferences would require a shift from a generic treatment approach towards personalized decision making. In this tesis, I showed that it is still difficult to make clinical decisions in the field of PD that are truly personalized. Personalized predictions models (i.e., models that provide a personalized, profile-based treatment predictions based on large amounts of data) are expected to improve personalized decision making for persons living with PD. However, there are important challenges that need to be addressed to turn large amounts of data into meaningful information in daily practice. This requires significant amounts of time, analytical skills in statistics and data interpretation, and clinical expertise.
Lieneke van den Heuvel (1990) obtained her bachelor in Biology in 2011, and after a pre-master year she started her Masters in Medicine at the Radboud University. In 2016 she received her medical degree and in this year she started the Neurology residency program at the Radboud university medical centre in Nijmegen. In 2018 she started her PhD-project under the supervision of prof. dr. Bastiaan R. Bloem and prof. dr. Anne M. Stiggelbout, resulting in this thesis.