Optimal drug treatment for children with IgA vasculitis nephritis: a systematic review and network meta-analysis
Year: 2025
Type: review
Study designs: Systematic Review, Meta-Analysis
Abstract: Background: At present, there are many treatment options for childhood IgA vasculitis nephritis (IgAVN), but the optimal treatment method remains unclear, and high-quality evidence to guide treatment decisions is still limited. This study identifies the best drugs for childhood IgAVN via Bayesian network meta-analysis (NMA). Methods: PubMed, Embase, Cochrane Library, Web of Science, CNKI, Wanfang, VIP, as well as Sinomed were comprehensively retrieved for pertinent randomized controlled trials (RCTs) examining various methods of treating childhood IgAVN with medication. NMA was enabled by R 4.2.2. The risk of bias was rated via the Cochrane Risk of Bias 2.0 (RoB 2.0). The effect size was estimated using the mean difference (MD), risk ratio (RR), or odds ratio (OR) and 95% confidence interval (CI). The effects of intervention methods were ranked using the surface under the cumulative ranking curve (SUCRA). The certainty of the evidence was examined via the Confidence in Network Meta-Analysis (CINeMA) approach. Possible publication bias was detected through funnel plots generated via Stata 18.0. Results: This study encompassed 73 RCTs. In comparison to standard of care (Soc), steroid therapy demonstrated the most favorable overall efficacy in IgAVN children (RR =1.17, 95% CI: 1.02-1.34). Leukotriene (LT) receptor antagonists were the most effective in reducing urinary protein (UP) levels (OR =13.28, 95% CI: 9.12-17.45)..Other therapies excelled in specific parameters. Conclusions: Steroids offer the most effective therapeutic approach for childhood IgAVN, though its safety profile needs further study. More research is required for clinical decisions.
Source: Translational Pediatrics
DOI: 10.21037/tp-2025-605
Authors: Ya Wang, Ying He, Fang Cheng, Fang Yang, Junjun Guo
Institution: Chengdu University of Traditional Chinese Medicine
Language: English
Subfield: Nephrology
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W7117370809
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