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Related Experiment Video

Updated: Feb 28, 2026

Imaging Features of Systemic Sclerosis-Associated Interstitial Lung Disease
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Systematic Review and Model-Based Meta-Analysis of Targeted Drugs for Systemic Sclerosis.

Marina Vaskeikina1, Yaroslav Ugolkov2,3,4, Boris Kireev2,3,4

  • 1Faculty of Medicine, Lomonosov Moscow State University, 119991 Moscow, Russia.

Pharmaceutics
|February 27, 2026
PubMed
Summary

This meta-analysis compared targeted therapies for systemic sclerosis (SSc). Guselkumab excelled in skin score improvement, while B-cell therapies like belimumab were best for lung function (FVC).

Keywords:
comparative effectivenessdrug efficacylongitudinal modelingmodel-based meta-analysissystemic sclerosistargeted therapies

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Area of Science:

  • Rheumatology and Immunology
  • Pharmacology and Drug Discovery

Background:

  • Systemic sclerosis (SSc) is a complex autoimmune fibrotic disease with varied presentations.
  • Targeted therapies offer new treatment avenues, but direct comparisons are difficult due to trial heterogeneity.

Purpose of the Study:

  • To systematically compare the efficacy of targeted therapies for systemic sclerosis (SSc).
  • To model treatment response trajectories for skin and lung function in SSc patients.

Main Methods:

  • Systematic literature search of RCTs in PubMed and ClinicalTrials.gov.
  • Longitudinal mixed-effect meta-model with Emax functions to analyze modified Rodnan skin score (mRSS) and forced vital capacity (FVC) trajectories.
  • Explicit modeling of between-study and between-treatment-arm variability.

Main Results:

  • Analyzed 32 RCTs (2036 patients, 23 agents). Guselkumab showed the greatest mRSS improvement.
  • B-cell therapies (belimumab, rituximab) were most effective for FVC; tocilizumab and nintedanib had moderate effects.
  • Half maximal treatment response developed around 27.5 weeks (6.3 months).

Conclusions:

  • Model-based meta-analysis offers a comparative overview of SSc targeted therapies.
  • Distinct efficacy patterns exist for skin vs. lung manifestations.
  • Findings may inform treatment selection and future clinical trial design.