Comparative Bibliometric Analysis of Herbal Medicine Research in Chinese and Iranian Complementary and Alternative Medicine (CAM) Clinical Trials

Background: Traditional medicine, rooted in ancient history, resurged due to concerns over synthetic pharmaceuticals’ adverse effects. This study goal was to conduct a bibliometric analysis of herbal medicine research in Iranian and Chinese CAM clinical trials to identify trends, patterns, and differences in research productivity. Materials and Methods: This bibliometric study compared Chinese and Iranian CAM clinical trials using Web of Science data. It focused on RCTs, applying search terms for CAM and Chinese or Iranian CAM, with exclusion criteria to filter out irrelevant publications. The dataset included author information, article details, keywords, and citation history. It calculated the Annual Growth Rate (AGR) and used visual tools like the Three-Field Plot to illustrate associations. Additionally, Lotka’s Law was applied to author productivity, and a co-citation collaboration network was analyzed using Bibliometrix r package. Results: Key findings for Iranian CAM include 71 documents by 342 authors with an average document age of 3.11 years. Chinese CAM featured 255 documents by 1857 authors with an average document age of 5.75 years. Iranian CAM showed a negative annual growth rate of -18.05%, while Chinese CAM had a positive rate of 5.65%. The included studies for Chinese CAM span from 2004 to 2024, while those for Iranian CAM range from 2015 to 2024. The most cited Iranian CAM document had 66 citations, and in Chinese CAM, “TONG XL, 2012” and “LIU XL, 2019” had the highest total citations. Decentralized research practices were observed in China, while Tehran and Shiraz universities led clinical trials in Iran. Conclusion: Our study indicates differing research trends in Iranian and Chinese herbal medicine. Iranian CAM research showed a declining trend, with Tehran and Shiraz universities leading clinical trials, while Chinese CAM research displayed a growing landscape with a more decentralized approach among authors.