Real-world data are defined as data relating to any aspect of a patient’s health status collected in the context of routine health surveillance and medical care delivery. Sources range from insurance billing claims through to electronic surveillance data (e.g., activity trackers). Real-world data derive from large populations in diverse clinical settings and thus can be extrapolated more readily than clinical trial data to patients in different clinical settings or with a variety of comorbidities. Real-world data are used to generate real-world evidence, which might be regarded as a “meta-analysis” of accumulated real-world data. Increasingly, regulatory authorities are recognizing the value of real-world data and real-world evidence, especially for rare diseases where it may be practically unfeasible to conduct randomized controlled trials. However, the quality of real-world evidence depends on the quality of the data collected which, in turn, depends on a correct pathological diagnosis and the homogeneous behaviour of a reliably defined and consistent disease entity. As each of the more than 80 varieties of soft tissue sarcoma (STS) types represents a distinct disease entity, the situation is exceedingly complicated. Discordant diagnoses, which affect data quality, present a major challenge for use of real-world data. As real-world data are difficult to collect, collaboration across sarcoma reference institutions and sophisticated information technology solutions are required before the potential of real-world evidence to inform decision-making in the management of STS can be fully exploited.