Systemic sclerosis: To subset or not to subset, that is the question

Area of Science:

• Rheumatology
• Immunology
• Internal Medicine

Background:

• Systemic sclerosis (SSc) is a complex autoimmune disease characterized by significant heterogeneity.
• Variability exists in autoantibody profiles, organ involvement, disease progression, and patient survival.
• Identifying homogeneous SSc patient subsets is crucial for research and clinical management.

Purpose of the Study:

• To review the historical development of SSc subsetting systems.
• To analyze the utility, strengths, and limitations of existing classification methods.
• To explore the emerging paradigm shift towards biologic and data-driven SSc subset classification.

Main Methods:

• Literature review of SSc subsetting systems.
• Analysis of clinically based subsetting approaches.
• Discussion of novel data-driven and biologic classification strategies.

Main Results:

• Clinically based SSc subsetting systems have historically informed patient care but have limitations.
• A paradigm shift is occurring, moving towards more sophisticated classification methods.
• New approaches consider biologic factors and employ data-driven analyses for improved accuracy.

Conclusions:

• The evolution of SSc subsetting reflects advancements in understanding disease heterogeneity.
• Modern approaches aim to enhance patient prognostication and personalize treatment strategies.
• Future classification systems must accommodate global SSc community needs and predictive capabilities.