Abstract
Epidemiological studies reporting demographic, clinical and serological factors predictive of various outcomes in systemic sclerosis (SSc) range from the prediction of mortality to the development and progression of disease manifestations. However, predicting the disease trajectory in the individual patient is a challenging but important step towards a stratified approach to disease management. Recent technological advances provide the opportunity for new subgroupings of disease based on risk stratification, through the systematic analysis of high-dimensional clinical data combined with genes, their transcription products and their corresponding translated proteins. In addition, these variables offer a rich vein of research to identify non-invasive biomarkers for predicting organ involvement and to assess disease activity and response to therapy. Selection of patients with a clinical phenotype or molecular signature relevant to the therapy under study combined with recent efforts to standardise outcome measures, show promise for improving clinical trial design and the identification of effective targeted therapies.
Collapse