Efficacy of baricitinib for the treatment of systemic lupus erythematosus patients: A meta-analysis of randomized controlled trials.

Abstract

Systemic lupus erythematosus (SLE) is an autoimmune disorder characterized by abnormal autoantibody production, inflammation, and organ damage. Most SLE treatment strategies aim to induce remission or reduce disease activity while avoiding flares. Baricitinib has been used effectively to manage various inflammatory diseases, and some randomized controlled trials (RCT) have shown that it is beneficial in treating SLE. The current study aims to assess the efficacy of baricitinib in treating SLE patients. Various databases such as PubMed, Scopus, and Science Direct were searched to obtain eligible studies for the present meta-analysis. Data such as baseline characteristics of patients, doses of the baricitinib, follow-up duration, and treatment outcome in the form of SLE responder index-4 (SRI-4) and lupus low disease activity state (LLDAS) were extracted. Combined odds ratio, 95% confidence interval, and probability values were calculated to study the efficacy of baricitinib in treating SLE patients. A p-value less than .05 was taken as significant. Comprehensive meta-analysis v3 was used for all analyses. Three articles were found eligible for the present meta-analysis comprising 614 patients with placebo, 614 SLE patients receiving 4 mg, and 621 patients with 2 mg of baricitinib. Meta-analysis revealed a beneficial effect of 4 mg baricitinib in SLE patients compared to placebo, as measured by an increase in the SRI-4 (p = .006, OR = 1.370) and LLDAS (p = .083, OR = 1.252) rates. In contrast to the placebo group, however, patients receiving 2 mg of baricitinib exhibited no significant improvement. The trial sequential analysis revealed the need for additional RCTs to determine the role of baricitinib in treating SLE patients. In treating SLE patients, administrating a higher dose of baricitinib (4 mg) may be effective. However, additional RCTs in different populations with larger sample sizes are required to validate our findings.