Multiobjective radiotherapy planning aims to capture all clinically relevant trade-offs between the various planning goals. This is accomplished by calculating a representative set of Pareto optimal solutions and storing them in a database. The structure of these representative Pareto sets is still not fully investigated. We propose two methods for a systematic analysis of multiobjective databases: principal component analysis and the isomap method. Both methods are able to extract the key trade-offs from a database and provide information which can lead to a better understanding of the clinical case and intensity-modulated radiation therapy planning in general.