Tian, JinhuiGao, YaZhang, JunhuaYang, ZhirongDong, ShengjieZhang, TiansongSun, FengWu, ShanshanWu, JiaruiWang, JunfengYao, LiangGe, LongLi, LunShi, ChunhuWang, QuanLi, JiangZhao, YeXiao, YueYang, FengwenFan, JinchunBao, ShisanSong, Fujian2024-07-192024-07-192021Tian J, Gao Y, Zhang J, et al. Progress and challenges of network meta-analysis. J Evid Based Med. 2021;14(3):218-231. doi:10.1111/jebm.12443https://hdl.handle.net/1805/42331In the past years, network meta-analysis (NMA) has been widely used among clinicians, guideline makers, and health technology assessment agencies and has played an important role in clinical decision-making and guideline development. To inform further development of NMAs, we conducted a bibliometric analysis to assess the current status of published NMA methodological studies, summarized the methodological progress of seven types of NMAs, and discussed the current challenges of NMAs.en-USPublisher PolicyBibliometric analysisDiagnostic test accuracyIndividual participant dataMethodological advancesNetwork meta-analysisArticle