To take cancer survivorship research to the next level, it's important to gain insight in trajectories of changing patient-reported outcomes and impaired recovery after cancer. This is needed as the number of survivors is increasing and a large proportion is confronted with changing health after treatment. Mechanistic research can facilitate the development of personalized risk-stratified follow-up care and tailored interventions to promote healthy cancer survivorship. We describe how these trajectories can be studied by taking the recently extended Dutch population-based Patient Reported Outcomes Following Initial treatment and Long term Evaluation of Survivorship (PROFILES) registry as an example. PROFILES combines longitudinal assessment of patient-reported outcomes with novel, ambulatory and objective measures (eg, activity trackers, blood draws, hair samples, online food diaries, online cognitive tests, weighing scales, online symptoms assessment), and cancer registry and pharmacy databases. Furthermore, we discuss methods to optimize the use of a multidomain data collection-like return of individual results to participants, which may improve not only patient empowerment but also long-term cohort retention. Also, advanced statistical methods are needed to handle high-dimensional longitudinal data (with missing values) and provide insight into trajectories of changing patient-reported outcomes after cancer. Our coded data can be used by academic researchers around the world. Registries like PROFILES, which go beyond boundaries of disciplines and institutions, will contribute to better predictions of who will experience changes and why. This is needed to prevent and mitigate long-term and late effects of cancer treatment and to identify new interventions to promote health.