An example analysis of network meta-analysis using R software for medical and health science research contexts

Authors

  • Gamon Savatsomboon Division of Management, Faculty of Accountancy and Management, Mahasarakham University
  • Kitti Krungkraipetch Department of Gynecology, Faculty of Medicine, Burapha University
  • Somsak Aphasitongsakun Division of Social and Administrative Pharmacy, Faculty of Pharmacy, Mahasarakham University
  • Chatchawarl Sarntipiphat Division of Orthopedics, Faculty of Medicine, Khon Kaen University
  • Ong-art Chanprasitchai Division of Financial Management, Faculty of Accountancy and Management, Mahasarakham University

Keywords:

R software, meta-analysis, network meta-analysis, medical and health science

Abstract

Research utilizing network meta-analysis (NMA) is widely published internationally. In the Thai context, some Thai researchers have published traditional meta-analysis works, referring to univariate meta-analysis. However, few researchers have published their works using NMA, particularly in the field of medical and health science. Additionally, few Thai researchers (if any) utilize the R software to conduct NMA for their research and publications. This indicates a notable practice gap. Therefore, the objective of this study is to demonstrate how to conduct NMA using the R software. R is freely available, globally accepted, and fully capable of analyzing NMA. Methodologically, secondary data is employed to illustrate our analysis. The dataset utilized is Dogliotti2014, which is freely available in R. NMA serves as the statistical method to analyze the data. In terms of analysis, the R procedures and codes are provided to demonstrate how to conduct NMA. Regarding results, different treatments (medications) yield varying outcomes. This leads to the conclusion that Antithrombotic drugs are the most effective in preventing strokes and should be considered for patients at risk of thromboembolism. In conclusion, the R software is fully capable of conducting comprehensive NMA. It is recommended that Thai medical and health science researchers utilize the R software for conducting NMA in their research and publications at both national and international levels.

References

Savatsomboon G, Aphasitongsakun S, Hantrakool P, et al. An application of R on analyzing meta-analysis for research: health science context. J Appl Inf Tech 2023;5(2),195–214. (in Thai)

Wongtangprasert S, Dilokthornsakul P. Network meta-analysis: The concept and its applications for healthcare professionals. Rama Med J 2017;40,48-58. (in Thai)

Chayaban W, Tippayakulpairoj D, Siripila S, et al. Network meta-analysis of teaching method influencing mathematics achievement of students. JEM-MSU 2020;27(1). (in Thai)

Balduzzi S, Rücker G, Nikolakopoulou A, et al. Netmeta: An R package for network meta-analysis using frequentist methods. J Stat Softw 2023;106(2). doi:10.18637/jss.v106.i02

Lee A. The development of network meta-analysis. J R Soc Med 2022;115(8),313-21

Harrer M. Chapter 12 network meta-analysis | doing meta-analysis in R n.d. https://bookdown.org/MathiasHarrer/Doing_Meta_Analysis_in_R/netwma.html

Viechtbauer W. Conducting meta-analyses in r with the metafor package. J Stat Softw 2010;36(3). doi:10.18637/jss.v036.i03

Cochrane methods comparing multiple interventions [Internet]. [cited 2024 Apr 20]. Available from: https://methods.cochrane.org/cmi/network-meta-analysis

Dogliotti A, Paolasso E, Giugliano R. P. Current and new oral antithrombotics in non-valvular atrial fibrillation: a network meta-analysis of 79,808 patients. Heart 2013;100(5),396-405.

R: Studies on antithrombotic treatments to prevent strokes. (n.d.). https://search.rproject.org/CRAN/refmans/metadat/html/dat.dogliotti2014.html

R Core Team (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.URL https://www.R-project.org/.

RStudio Team (2020). RStudio: Integrated development for R. RStudio, PBC, Boston, MA URL http://www.rstudio.com/.

Wickham H, François R, Henry L, et al. Dplyr: A grammar of data manipulation 2023. https://dplyr.tidyverse.org, https://github.com/tidyverse/dplyr.

StataCorp. STATA for Windows. Version 18.0. College Station, TX: StataCorp; 2023.

Biostat. CMA for Windows. Version 4.0. Englewood, NJ: StataCorp; 2023.

Downloads

Published

2024-04-30

How to Cite

1.
Savatsomboon G, Krungkraipetch K, Aphasitongsakun S, Sarntipiphat C, Chanprasitchai O- art. An example analysis of network meta-analysis using R software for medical and health science research contexts. J Med Health Sci [Internet]. 2024 Apr. 30 [cited 2024 Jul. 1];31(1):153-67. Available from: https://he01.tci-thaijo.org/index.php/jmhs/article/view/266860

Issue

Section

Short communication (บทความวิจัยอย่างสั้น)