Immunological coagulation dual axis stratification identifies ultra high-risk phenotypes in systemic sclerosis

Systemic sclerosis is a heterogeneous autoimmune disease characterized by complex interplay among immune activation, inflammation, coagulation, and fibrinolysis. This study aimed to construct a comprehensive immune-inflammation-coagulation-fibrinolysis (IICF) network and to evaluate its topological features and prognostic value across distinct organ involvement phenotypes.

A total of 287 patients with systemic sclerosis were retrospectively enrolled, including 166 with isolated SSc, 85 with concomitant interstitial lung disease (ILD), 18 with pulmonary hypertension (PH), and 18 with both ILD and PH. Twelve composite indices encompassing IICF pathways were calculated. LASSO-Cox regression was employed to build a multi-index prognostic score, K-means clustering was performed to identify molecular endotypes, and patients were stratified using optimal cut-off values of the Systemic Immune-Inflammation Index (SII) and the D-dimer-to-Platelet Ratio (DPR) for dual-axis survival analysis.

Immune-coagulation dual-axis stratification revealed that patients with concurrent elevation of both SII and DPR had a 7.41-fold higher mortality risk than those with dual-low levels (HR 7.41, 95% CI 2.09-26.30, P = 0.002), whereas elevation of either index alone did not reach statistical significance. K-means clustering identified three IICF molecular endotypes, which showed incomplete concordance with the presence of ILD or PH. The multi-index prognostic score yielded an area under the curve of 0.747 for mortality prediction, surpassing the Prognostic Nutritional Index (0.693) and the Neutrophil-to-Lymphocyte Ratio (0.675).

Adverse outcomes in systemic sclerosis are driven by systemic network disequilibrium rather than isolated pathway aberrations, with synergistic interplay between immune activation and coagulation dysregulation representing a pivotal mechanism. IICF-based dual-axis stratification and multi-index scoring provide a quantifiable approach for precision phenotyping and may inform stratified therapeutic decision-making.