The current diagnostic classification system for systemic sclerosis (SSc) limits the understanding of its heterogeneity, thus making it important for future disease classification to integrate innovative approaches, according to a review published in Current Opinions in Rheumatology.

While SSc has historically been described as either “limited” or “diffuse,” based on skin involvement, recent studies have identified organ involvement, serology, and gene expression profiles as more powerful prognostic indicators than phenotype. Better classification of disease subgroups can facilitate treatment efforts and allow for better risk stratification.  

Systemic sclerosis is a severe rheumatologic condition with highly heterogeneous presentations. Classification criteria proposed in 1988 dictate the current understanding of SSc subgroups. Revised in 2001, the guidelines define 2 main subsets of SSc based on the extent of skin fibrosis: diffuse cutaneous SSc (dcSSc), affecting the trunk and proximal limbs; and limited cutaneous SSc (lcSSc), affecting the hands, face, feet, and forearms. According to review authors, this classification system may be insufficient in predicting disease outcomes and treatment response. Recent research has shown that the diversity of SSc may warrant a more complex classification system.


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Recent research has shown that skin involvement is not a reliable indicator of disease activity in SSc. In a study of 398 patients followed up for 15 years, compared with phenotypes, the presence of organ damage was a more powerful indicator of disease outcomes in lcSSc and dcSSc. Other studies have identified serologic profiles as important indicators of disease prognosis. Specifically, antitopoisomerase-I positivity was associated with greater organ damage and poorer survival across several trials.

In a 2019 study that used machine learning to classify patients with SSc, 6 different homogenous groups were generated based on skin involvement, serology, and organ damage. Another study published in 2020 proposed a 7-group classification system that combined autoantibody profiles with diffuse vs limited skin involvement. This new system was more precise in identifying patients with interstitial lung disease, major organ-based complications, and mortality.

Translational studies using “omic” approaches have been able to distinguish healthy individuals from patients with SSc. These omic profiles use serum metabolic profiles, transcriptomic signatures from skin biopsies, and other gene expression markers to classify patients with SSc. While these classification systems are in their nascent stages, they may inform future efforts to better describe SSc subtypes.

In a study of abatacept for the treatment of SSc, classification of patients by gene expression subsets revealed that abatacept was superior to placebo in patients with inflammatory SSc; however, when patients were classified as having either diffuse or limited SSc, abatacept did not emerge as more effective than placebo.

While the historical diffuse/limited classification system has had utility in clinical practice, a more granular system may be necessary. Recent studies have failed to confirm a parallelism between the extent of skin involvement and clinical outcomes, such as organ damage. Instead, disease profiles integrating clinical and biological measures may better classify patients with SSc. Improved classification of the disease can allow for better targeted treatment and improved enrollment in clinical trials.

“It seems critical to pursue this [new] characterization, always bearing in mind that the identified subgroups must be clinically meaningful and relevant in terms of pathophysiology,” the review authors concluded. “Everyday tools, readily available, should be standardized and could also be integrated into these classifications in order to keep them practical and easy to use.”

Disclosure: Study authors declared affiliations with the pharmaceutical industry. Please see the original reference for a full list of authors’ disclosures.

Reference

Sobanski V, Lescoat A, Launay D. Novel classifications for systemic sclerosis: challenging historical subsets to unlock new doors. Published online September 15, 2020. Curr Opin Rheumatol. doi:10.1097/BOR.0000000000000747