Systematic Review and Model-Based Meta-Analysis of Targeted Drugs for Systemic Sclerosis

Background: Systemic sclerosis (SSc) is a complex autoimmune fibrotic disorder marked by heterogeneous clinical features and multiple pathophysiological mechanisms. The rapid emergence of targeted therapies, aimed at selectively modulating molecular targets, has expanded treatment options; however, making direct efficacy comparisons remains challenging due to the variability in trial designs, endpoints, and patient populations. Methods: A systematic search of PubMed and ClinicalTrials.gov identified randomized controlled trials (RCTs) evaluating targeted therapies in SSc. A longitudinal mixed-effect meta-model incorporating Emax structural functions characterized treatment response trajectories for the modified Rodnan skin score (mRSS) and forced vital capacity (FVC). Between-study and between-treatment-arm variability were explicitly modeled to account for heterogeneity. Results: A total of 32 RCTs with 2036 patients and 23 targeted agents were analyzed. Guselkumab, an anti-IL-23 antibody, showed the greatest effect on mRSS, followed by tofacitinib, inebilizumab, and baricitinib. For FVC, B-cell-targeted therapies, with belimumab and rituximab, demonstrated the highest efficacy, while tocilizumab and nintedanib had more moderate effects. Time to 50% maximal response was approximately 27.5 weeks, indicating a 6.3-month period for half treatment response development. Conclusions: This model-based meta-analysis provides a broad comparison of targeted therapies in SSc, highlighting distinct efficacy patterns for skin versus lung involvement and offering hypothesis-generating insights that may support treatment selection and the design of future clinical trials.