Abstract
OBJECTIVES: We appraised the methodological and reporting quality of randomised controlled clinical trials (RCTs) evaluating the efficacy and safety of Chinese herbal medicine (CHM) in patients with rheumatoid arthritis (RA). DESIGN: For this systematic review, electronic databases were searched from inception until June 2015. The search was limited to humans and non-case report studies, but was not limited by language, year of publication or type of publication. Two independent reviewers selected RCTs, evaluating CHM in RA (herbals and decoctions). Descriptive statistics were used to report on risk of bias and their adherence to reporting standards. Multivariable logistic regression analysis was performed to determine study characteristics associated with high or unclear risk of bias. RESULTS: Out of 2342 unique citations, we selected 119 RCTs including 18 919 patients: 10 108 patients received CHM alone and 6550 received one of 11 treatment combinations. A high risk of bias was observed across all domains: 21% had a high risk for selection bias (11% from sequence generation and 30% from allocation concealment), 85% for performance bias, 89% for detection bias, 4% for attrition bias and 40% for reporting bias. In multivariable analysis, fewer authors were associated with selection bias (allocation concealment), performance bias and attrition bias, and earlier year of publication and funding source not reported or disclosed were associated with selection bias (sequence generation). Studies published in non-English language were associated with reporting bias. Poor adherence to recommended reporting standards (<60% of the studies not providing sufficient information) was observed in 11 of the 23 sections evaluated. LIMITATIONS: Study quality and data extraction were performed by one reviewer and cross-checked by a second reviewer. Translation to English was performed by one reviewer in 85% of the included studies. CONCLUSIONS: Studies evaluating CHM often fail to meet expected methodological criteria, and high-quality evidence is lacking.