The objectives of the study were to (1) determine the sensitivity of EULAR/ACR criteria to properly classify myositis-specific autoantibody (MSA) positive myositis patients, (2) describe the phenotype and muscle involvement over time in different MSA-positive patients, and (3) compare MSAs with the EULAR/ACR subgroups to predict clinical phenotypes.
The study included 524 MSA-positive myositis patients from the Johns Hopkins Myositis Center. Each patient was classified using the EULAR/ACR classification criteria. Patient phenotypes were summarized using factor analysis of mixed data (FAMD). We compared the ability of MSAs with the EULAR/ACR subgroups to predict the phenotype of patients by applying the Akaike information criterion (AIC) and the Bayesian information criteria (BIC) to the linear regression models.
Overall, 91% of MSA-positive patients met EULAR/ACR criteria to be classified as myositis. However, 20% of anti-HMGCR and 50% of anti-PL7 patients were incorrectly classified as not myositis. Furthermore, ~10% of anti-SRP and anti-HMGCR patients were misclassified as having inclusion body myositis. FAMD demonstrated that patients within each MSA-defined group had similar phenotypes. Application of both the AIC and BIC to the linear regression models revealed that MSAs better predict myositis phenotypes than the subgroups defined by the EULAR/ACR criteria.
Although the EULAR/ACR criteria successfully classified 91% of MSA-positive myositis patients, certain MSA-defined subgroups, including those with autoantibodies against HMGCR, SRP, and PL7, are frequently misclassified. In myositis patients with MSAs, autoantibodies outperform the EULAR/ACR-defined subgroups to predict clinical phenotypes. These findings underscore the need to include MSAs in a revised myositis classification scheme.