Efficacy and safety of Chinese botanical drug decoctions for migraine: a Bayesian network meta-analysis
Abstract
Background: Migraine is a common neurological disorder that substantially affects patients' quality of life. Chinese botanical drug decoctions are used in migraine management; however, the comparative efficacy and safety of different decoctions remain unclear. Therefore, this study aimed to compare multiple Chinese botanical drug decoctions for migraine using a Bayesian network meta-analysis.
Methods: Seven electronic databases (PubMed, Embase, Cochrane Library, Web of Science, CNKI, Wanfang, and VIP) were systematically searched from inception to 20 October 2025. Randomized controlled trials evaluating Chinese botanical drug decoctions for migraine were included. Risk of bias was assessed using the ROB 2.0 tool. A Bayesian network meta-analysis was conducted using R software with the gemtc package. Four Markov chains were run simultaneously, with 50,000 iterations and a burn-in period of 20,000 iterations to ensure model convergence. Treatment ranking probabilities were estimated using the surface under the cumulative ranking curve (SUCRA).
Results: A total of 57 randomized controlled trials involving 6,005 patients were included. Network meta-analysis suggested that Sanpian Decoction (SPT) was associated with greater reductions in visual Analog Scale (VAS) scores, while Xuefu Zhuyu Decoction (XFZYT) ranked highest for reducing headache frequency and duration. Tongqiao Huoxue Decoction (TQHXT) had the highest probability of being among the most effective interventions based…
How strong is the evidence?
Evidence Hub reads this as a meta-analysis, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid. Reported size: 6,005 participants or records.
Read the paper
Related studies
- Calcium Ions in the Physiology and Pathology of the Central Nervous System
- AI-powered in silico twins: redefining precision medicine through simulation, personalization, and predictive healthcare
- In silico functional, structural and pathogenicity analysis of missense single nucleotide polymorphisms in human MCM6 gene
- In Silico drug repurposing pipeline using deep learning and structure based approaches in epilepsy
- Targeting serotonin receptors with phytochemicals – an in-silico study
- In silico exploration of anti-prostate cancer compounds from differential expressed genes
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.