[Research status of Meta-epidemiology and its application in TCM]

Meta-epidemiology is an emerging research approach that incorporates systematic reviews(SRs) or Meta-analyses to examine the impact of specific characteristics of clinical studies on observed effects. It aims to identify potential sources of bias and to accurately estimate between-trial heterogeneity and changes in average bias within Meta-analyses, thereby enhancing the quality of primary studies and SRs. As the methodological framework of Meta-epidemiology continues to mature and the demand for precise evidence linking trial characteristics with heterogeneity increases in the field of TCM, the application value of Meta-epidemiology has become increasingly prominent. This article systematically elaborates on the core methodological characteristics of Meta-epidemiological studies that take SRs or Meta-analyses as the unit of analysis. By integrating multidimensional visual analyses, including publication volume characteristics, national and regional collaboration networks, author collaboration networks, and keyword co-occurrence and clustering, the development trends and research hotspots in this field are comprehensively mapped. The results indicate that, in recent years, Meta-epidemiological research has developed rapidly worldwide, with increasingly close international collaboration between the United Kingdom and the United States. Research themes have mostly focused on disease areas such as osteoarthritis, acute exacerbations of chronic obstructive pulmonary disease, and cardiovascular diseases. On this basis, the article further explores the application value of Meta-epidemiology in the field of TCM. Using acupuncture and moxibustion as an example, it analyzes the adaptability of this approach in addressing key issues in TCM clinical trials, such as high heterogeneity and difficulties in risk-of-bias assessment. The study aims to establish a more robust methodological framework for TCM research and to support the generation of higher-quality evidence and more reliable inference.