荟萃分析
医学
皮肤病科
系统性红斑狼疮
皮肤红斑狼疮
红斑狼疮
免疫学
内科学
抗体
疾病
作者
Laura Bokor,Katalin Martyin,Máté Krebs,Noémi Ágnes Galajda,Fanni Adél Meznerics,Bence Szabó,Péter Hegyi,Kende Lőrincz,Norbert Kiss,András Bánvölgyi,Bernadett Hídvégi
标识
DOI:10.1016/j.autrev.2024.103723
摘要
BACKGROUND: Novel therapies for cutaneous lupus erythematosus (CLE) and systemic lupus erythematosus (SLE) demonstrated efficacy and safety in previous trials. However, data on the comparison of these treatments is still lacking, limiting their integration into clinical practice. Therefore, our aim is to perform a systematic review and network meta-analysis to compare the efficacy and safety of novel systemic therapies in CLE. METHODS: A systematic search was performed across PubMed, Embase, and CENTRAL on November 25, 2023, to identify studies involving patients with CLE or SLE with active skin involvement treated with novel systemic therapies. The primary outcomes assessed were the proportion of patients achieving the Cutaneous Lupus Erythematosus Disease Area and Severity Index-50 (CLASI-50), the change in CLASI-A, the occurrence of adverse events (AEs), and serious adverse events (SAEs). RESULTS: 18,280 records were retrieved, of which 53 met the inclusion criteria. Deucravacitinib showed significantly greater efficacy in achieving the CLASI50 compared to placebo (OR: 8.28, 95 % CI: 2.22-30.91). Both litifilimab (OR: 2.54, 95 % CI: 1.20-5.40) and anifrolumab (OR: 2.25, 95 % CI: 1.23-4.14) were also significantly more effective than placebo. No significant differences were observed in the occurrence of AEs and SAEs between these therapeutics and placebo. CONCLUSION: Anifrolumab and litifilimab are effective and safe treatment options in CLE. However, deucravacitinib demonstrated superior efficacy and safety with fewer adverse events compared to anifrolumab. CLE patients who have shown an inadequate response to first- and second-line treatments may benefit from the incorporation of deucravacitinib into their treatment regimens.
科研通智能强力驱动
Strongly Powered by AbleSci AI