Evaluation of a screening algorithm to detect systemic sclerosis-related myopathy

Area of Science:

• Rheumatology
• Neurology
• Immunology

Background:

• Systemic sclerosis (SSc) can involve muscles, with prevalence varying widely.
• Early diagnosis of inflammatory myopathy (IM) in SSc is crucial for timely treatment.
• A standardized screening approach for SSc-related muscle involvement is lacking.

Purpose of the Study:

• To evaluate a novel screening algorithm for detecting muscle involvement in systemic sclerosis (SSc).
• To assess the efficacy of the proposed algorithm in identifying inflammatory myopathy (IM).

Main Methods:

• Consecutive SSc patients in the Australian Scleroderma Cohort Study (ASCS) were monitored for myopathy symptoms (weakness, elevated creatine kinase).
• A subset of patients underwent further assessment including myositis immunoblot and muscle MRI if initial signs were present.
• Muscle biopsy was performed for positive screening results.

Main Results:

• The screening algorithm identified biopsy-proven IM in 9.9% of screened SSc patients.
• Detection of IM increased approximately 4.5-fold compared to routine care.
• Early diagnosis facilitated timely immunomodulatory therapy, leading to improved muscle strength.

Conclusions:

• The developed screening algorithm effectively identifies muscle involvement in SSc patients.
• This approach allows for earlier diagnosis and treatment of IM, potentially preventing disease progression.
• The algorithm helps differentiate inflammatory from non-inflammatory myopathies, avoiding unnecessary immunosuppression.