Methodological quality of network meta-analyses of Chinese herbal medicine could be improved: an evidence mapping.

Network meta-analyses (NMAs) are essential for comparing multiple Chinese herbal medicine (CHM) interventions, but their methodological rigor requires evaluation. We systematically searched five databases for CHM NMAs published from inception to June 2025. Studies were included if they were English-language, SCI/SSCI-indexed NMAs evaluating at least one pharmacopoeia-listed CHM. Conference abstracts, editorials, expert opinions, conference proceedings, case reports, and Meta-analyses were excluded. Two reviewers independently screened studies, extracted data, and appraised methodological quality using AMSTAR 2. Factors associated with quality (dichotomized as high/moderate vs. low/critically low) were examined using logistic regression. Of 1,016 identified records, 212 NMAs were included, encompassing 13,575 primary studies and 1,302,518 participants. Methodological quality was generally low: 1.42% were high, 5.19% moderate, 61.32% low, and 32.08% critically low. Common shortcomings involved literature search comprehensiveness, listing of excluded studies, reporting of funding sources for included trials, and assessment of risk of bias impact. In multivariable analysis, a larger number of authors (OR = 1.177, 95% CI: 1.014-1.366, p = 0.032) was associated with higher quality. An association was also observed for non-China corresponding author country (OR = 7.914, 95% CI: 1.360-46.065, p = 0.021), although the wide confidence interval warrants cautious interpretation. The assessment was based on AMSTAR 2, which is not NMA-specific. Restriction to SCI/SSCI journals may have excluded lower-quality studies. This work was supported by grants from the National Natural Science Foundation of China (82,305,209, 82,505,508) and other local funds. This systematic review was not preregistered. The methodological quality of published CHM NMAs is predominantly low. Enhancing team size and collaboration, alongside strict adherence to core methodological standards, is crucial for improving the reliability and utility of future evidence syntheses in this field.