Table 1_Identifying inflammatory phenotypes associated with lung involvement in systemic sclerosis: k-means clustering approach.docx

Objectiveto assess the prognostic impact of clusters of hematologic and biochemical indices on interstitial lung disease (ILD) and respiratory damage associated with systemic sclerosis (SSc) MethodsDesign: 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. ResultsAmong 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). ConclusionCRP-based variables seem to be better predictors of SSc-ILD and respiratory damage than hematological indices.