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. 2021 May 3;21(1):144.
doi: 10.1186/s12911-021-01470-5.

A bibliometric analysis of global research output on network meta-analysis

Jiyuan Shi #  1 , Ya Gao #  2 , Liu Ming  2 , Kelu Yang  1 , Yue Sun  3 , Ji Chen  4 , Shuzhen Shi  2 , Jie Geng  5 , Lun Li  6 , Jiarui Wu  7 , Jinhui Tian  8   9   10
Affiliations

A bibliometric analysis of global research output on network meta-analysis

Jiyuan Shi et al. BMC Med Inform Decis Mak. .

Abstract

Background: Network meta-analysis (NMA) has been widely used in the field of medicine and health, but the research topics and development trends are still unclear. This study aimed to identify the cooperation of countries and institutes and explore the hot topics and future prospects in the field of NMA.

Methods: Data of publications were downloaded from the Web of Science Core Collection. We used CiteSpace V, HistCite 2.1, and Excel 2016 to analyze literature information, including years, journals, countries, institutes, authors, keywords, and co-cited references.

Results: NMA research developed gradually before 2010 and rapidly in the following years. 2846 NMA studies were published in 771 journals in six languages. The PLoS One (110, 3.9%) was the most productive journal, and N Engl J Med (5904 co-citations) was the most co-cited journal. The most productive country was the United States (889, 31%) and the most productive institute was the University of Bristol (113, 4.0%). The active collaborations were observed between developed countries and between productive institutes. Of the top 10 authors, four were from the UK, and among the top 10 co-cited authors, six were from the UK. Randomized evidence, oral anti-diabetic drugs, coronary artery bypass, certolizumab pegol, non-valvular atrial fibrillation, and second-line antihyperglycemic therapy were the hot topics in this field.

Conclusions: NMA studies have significantly increased over the past decade, especially from 2015 to 2017. Compared with developing countries, developed countries have contributed more to these publications and have closer cooperation, indicating that cooperation between developed and developing countries should be further strengthened. The treatment of diabetes, cardiovascular diseases, and immune rheumatism are the main hot topics.

Keywords: Bibliometric analysis; CiteSpace; Development trends; Hotspots; Network meta-analyses; Web of Science.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
The flowchart of the screening process
Fig. 2
Fig. 2
Publication years and growth forecast for NMA research
Fig. 3
Fig. 3
The dual-map overlay of journals related to NMA research
Fig. 4
Fig. 4
The network map of countries for NMA research
Fig. 5
Fig. 5
The network map of institutes for NMA research
Fig. 6
Fig. 6
Top 36 references with strong citation bursts. Note The red bars mean some references cited frequently; the green bars were references cited infrequently
Fig. 7
Fig. 7
The network map of keywords for NMA research
See this image and copyright information in PMC

References

    1. Lumley T. Network meta-analysis for indirect treatment comparisons. Stat Med. 2002;21(16):2313–2324. doi: 10.1002/sim.1201. - DOI - PubMed
    1. Zhao H, Hodges JS, Ma H, Jiang Q, Carlin BP. Hierarchical Bayesian approaches for detecting inconsistency in network meta-analysis. Stat Med. 2016;35(20):3524–3536. doi: 10.1002/sim.6938. - DOI - PubMed
    1. Gao Y, Ge L, Ma X, Shen X, Liu M, Tian J. Improvement needed in the network geometry and inconsistency of Cochrane network meta-analyses: a cross-sectional survey. J Clin Epidemiol. 2019;113:214–227. doi: 10.1016/j.jclinepi.2019.05.022. - DOI - PubMed
    1. Li L, Tian J, Tian H, Moher D, Liang F, Jiang T, Yao L, Yang K. Network meta-analyses could be improved by searching more sources and by involving a librarian. J Clin Epidemiol. 2014;67(9):1001–1007. doi: 10.1016/j.jclinepi.2014.04.003. - DOI - PubMed
    1. Lu G, Ades AE. Combination of direct and indirect evidence in mixed treatment comparisons. Stat Med. 2004;23(20):3105–3124. doi: 10.1002/sim.1875. - DOI - PubMed

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