Identifying inflammatory phenotypes associated with lung involvement in systemic sclerosis: k-means clustering approach.

OBJECTIVE

to assess the prognostic impact of clusters of hematologic and biochemical indices on interstitial lung disease (ILD) and respiratory damage associated with systemic sclerosis (SSc).

METHODS

Design: We conducted a cross-sectional, uncontrolled study. Participants and Settings: a cohort of patients with SSc (2013 ACR/EULAR criteria) were enrolled in the rheumatology unit of a tertiary hospital in southern Spain. Primary and secondary outcome measures: The primary outcomes were the presence of SSc-ILD and respiratory damage, assessed via the Scleroderma Clinical Trials Consortium Damage Index (SCTC-DI). Inflammatory biomarkers, including both CRP and hematological indices, were obtained. Patients were grouped based on inflammatory phenotypes derived from longitudinal CRP averages and through principal component analysis (PCA) with K-means clustering of cross-sectional variables. Multivariate models were constructed to identify factors associated with SSc-ILD and respiratory damage.

RESULTS

Among 83 patients with SSc, 33.7% had ILD, 30.1% had respiratory damage, and 28.9% were receiving immunosuppressive therapy. A persistent inflammatory phenotype during follow-up was associated with non-Caucasian ethnicity (OR 14.0) and SSc-ILD (OR 17.9). Cross-sectional inflammatory clusters were linked to SSc-ILD (OR 12.8) and damage measured by SCTC-DI (OR 1.2). PC-2, derived from CRP-based variables, was a better predictor of SSc-ILD (OR 3.0) than PC-1, which was based on hematological indices (OR 0.5, non-significant), especially in the presence of anti-Scl70+ antibodies (OR 19.1) and immunosuppressants (OR 42.2). The only variables associated with respiratory damage were average CRP during follow-up (OR 1.2), anti-Scl70+ (OR 7.7), and glucocorticoids (OR 0.2).

CONCLUSION

CRP-based variables seem to be better predictors of SSc-ILD and respiratory damage than hematological indices.