The challenges and controversies of measuring disease activity in systemic sclerosis. Issue 2 (June 2018)

• Record Type: Journal Article
• Authors: Ross, Laura; Baron, Murray; Nikpour, Mandana
• Is Part Of: Journal of scleroderma and related disorders. Volume 3:Issue 2(2018)
• Page Start: 115
• Page End: 121
• Publication Date: 2018-06
• Subjects: Activity index -- disease activity -- outcome measure -- systemic sclerosis (scleroderma); Scleroderma (Disease) -- Periodicals; Systemic scleroderma -- Periodicals; Fibrosis -- Periodicals; 616.544
• DOI: 10.1177/2397198318765061
• Languages: English
• ISSNs: 2397-1983

Abstract

Major alteration of the natural history of systemic sclerosis is limited with current treatments, and the development of novel therapies has been hampered, in part, by the lack of fully validated multi-system outcome measures. There remains a lack of consensus as to the very definition of systemic sclerosis disease activity, complicating efforts to measure activity in clinical trials. Previously published multi-system measures of disease status are yet to be fully validated according to the Outcome Measures in Rheumatology (OMERACT) filter. There is currently significant research interest in developing new systemic sclerosis–specific measures to better describe and compare patient cohorts and measure therapeutic responses in clinical trials. An accurate measure of disease activity in systemic sclerosis will facilitate the enrichment of clinical trials with patients who have active disease, targeting a group of patients most likely to benefit from therapeutic intervention. In addition, following on from successes in other rheumatic conditions, a state of low disease activity, measured by an activity index, may become a clinical trial end point and therapeutic target. The Scleroderma Clinical Trials Consortium has undertaken to develop a definition of disease activity and fully validate a new systemic sclerosis activity index. The Scleroderma Clinical Trials Consortium Activity Index will be developed using consensus and data-driven methods and is envisaged to be widely used in research and clinical settings.