PT  - JOURNAL ARTICLE
AU  - Tatiana Nevskaya
AU  - Janet E.  Pope
AU  - Matthew A.  Turk
AU  - Jenny Shu
AU  - April Marquardt
AU  - Frank  van den Hoogen
AU  - Dinesh Khanna
AU  - Jaap Fransen
AU  - Marco Matucci-Cerinic
AU  - Murray Baron
AU  - Christopher P.  Denton
AU  - Sindhu R.  Johnson
TI  - Systematic Analysis of the Literature in Search of Defining Systemic Sclerosis Subsets
AID  - 10.3899/jrheum.201594
DP  - 2021 May 15
TA  - The Journal of Rheumatology
PG  - jrheum.201594
4099  - http://www.jrheum.org/content/early/2021/08/26/jrheum.201594.short
4100  - http://www.jrheum.org/content/early/2021/08/26/jrheum.201594.full
AB  - Objective Systemic sclerosis (SSc) is a multisystem disease with heterogeneity in presentation and prognosis. An international collaboration to develop new SSc subset criteria is underway. Our objectives were to identify systems of SSc subset classification and synthesize novel concepts to inform development of new criteria. Methods Medline, Cochrane MEDLINE, the Cumulative Index to Nursing and Allied Health Literature, EMBASE, and Web of Science were searched from their inceptions to December 2019 for studies related to SSc subclassification, limited to humans and without language or sample size restrictions. Results Of 5686 citations, 102 studies reported original data on SSc subsets. Subset classification systems relied on extent of skin involvement and/or SSc-specific autoantibodies (n = 61), nailfold capillary patterns (n = 29), and molecular, genomic, and cellular patterns (n = 12). While some systems of subset classification confer prognostic value for clinical phenotype, severity, and mortality, only subsetting by gene expression signatures in tissue samples has been associated with response to therapy. Conclusion Subsetting on extent of skin involvement remains important. Novel disease attributes including SSc-specific autoantibodies, nailfold capillary patterns, and tissue gene expression signatures have been proposed as innovative means of SSc subsetting.