Clustering and Evolving Concepts for Subclassification

Systemic sclerosis is an extremely heterogeneous disease, with a large variability of clinical presentations and difficult-to-predict courses in patients. Different classifications have been proposed to gather patients into homogeneous groups (of the disease itself or the different subtypes). These concepts have allowed a more rigorous analysis of patient data. Recent studies have shown that the classifications are not set in stone, as improvements are still possible, especially thanks to high-throughput analysis techniques and advances in computer science that allow integrative analyses encompassing more and more dimensions of the disease.