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Comparative efficacy and safety of traditional Chinese patent medicine for the treatment of type 2 diabetes mellitus: A Bayesian network meta-analysis protocol
BACKGROUND: At present, the prevalence of type 2 diabetes mellitus (T2DM) has become a major public health issue throughout the world, especially in developing countries. Notably, traditional Chinese patent medicines (TCPMs) are of great significance in the treatment of T2DM combined with convention...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7535762/ https://www.ncbi.nlm.nih.gov/pubmed/33019468 http://dx.doi.org/10.1097/MD.0000000000022564 |
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author | Li, Jie Zhao, Sen Huang, Yanqin Li, Chuancheng Li, Bing Xu, Yunsheng |
author_facet | Li, Jie Zhao, Sen Huang, Yanqin Li, Chuancheng Li, Bing Xu, Yunsheng |
author_sort | Li, Jie |
collection | PubMed |
description | BACKGROUND: At present, the prevalence of type 2 diabetes mellitus (T2DM) has become a major public health issue throughout the world, especially in developing countries. Notably, traditional Chinese patent medicines (TCPMs) are of great significance in the treatment of T2DM combined with conventional Western medicine therapy. However, there is a lack of comparison among all the current common TCPMs for treating T2DM. Therefore, this study intends to explore the efficacy and safety of different TCPMs against T2DM through the Bayesian network meta-analysis (NMA). METHODS: We will conduct a comprehensive and systematic search for randomized controlled trials (RCTs) of TCPM for the treatment of T2DM in both Chinese and English databases published till August 2020. Two researchers will be responsible for screening eligible literature, extracting data, and assessing the risk of bias of included studies independently. Then, pairwise meta-analyses and Bayesian network meta-analyses will be conducted to assess all available evidence. In the end, data will be analyzed using STATA15.0 and WinBUGS1.4.3 software. CONCLUSION: This study will compare the efficacy and safety of different TCPMs against T2DM in detail. Our findings will provide a reliable evidence for selecting clinical treatment program and guideline development of T2DM. |
format | Online Article Text |
id | pubmed-7535762 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-75357622020-10-14 Comparative efficacy and safety of traditional Chinese patent medicine for the treatment of type 2 diabetes mellitus: A Bayesian network meta-analysis protocol Li, Jie Zhao, Sen Huang, Yanqin Li, Chuancheng Li, Bing Xu, Yunsheng Medicine (Baltimore) 3800 BACKGROUND: At present, the prevalence of type 2 diabetes mellitus (T2DM) has become a major public health issue throughout the world, especially in developing countries. Notably, traditional Chinese patent medicines (TCPMs) are of great significance in the treatment of T2DM combined with conventional Western medicine therapy. However, there is a lack of comparison among all the current common TCPMs for treating T2DM. Therefore, this study intends to explore the efficacy and safety of different TCPMs against T2DM through the Bayesian network meta-analysis (NMA). METHODS: We will conduct a comprehensive and systematic search for randomized controlled trials (RCTs) of TCPM for the treatment of T2DM in both Chinese and English databases published till August 2020. Two researchers will be responsible for screening eligible literature, extracting data, and assessing the risk of bias of included studies independently. Then, pairwise meta-analyses and Bayesian network meta-analyses will be conducted to assess all available evidence. In the end, data will be analyzed using STATA15.0 and WinBUGS1.4.3 software. CONCLUSION: This study will compare the efficacy and safety of different TCPMs against T2DM in detail. Our findings will provide a reliable evidence for selecting clinical treatment program and guideline development of T2DM. Lippincott Williams & Wilkins 2020-10-02 /pmc/articles/PMC7535762/ /pubmed/33019468 http://dx.doi.org/10.1097/MD.0000000000022564 Text en Copyright © 2020 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by/4.0 This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/licenses/by/4.0 |
spellingShingle | 3800 Li, Jie Zhao, Sen Huang, Yanqin Li, Chuancheng Li, Bing Xu, Yunsheng Comparative efficacy and safety of traditional Chinese patent medicine for the treatment of type 2 diabetes mellitus: A Bayesian network meta-analysis protocol |
title | Comparative efficacy and safety of traditional Chinese patent medicine for the treatment of type 2 diabetes mellitus: A Bayesian network meta-analysis protocol |
title_full | Comparative efficacy and safety of traditional Chinese patent medicine for the treatment of type 2 diabetes mellitus: A Bayesian network meta-analysis protocol |
title_fullStr | Comparative efficacy and safety of traditional Chinese patent medicine for the treatment of type 2 diabetes mellitus: A Bayesian network meta-analysis protocol |
title_full_unstemmed | Comparative efficacy and safety of traditional Chinese patent medicine for the treatment of type 2 diabetes mellitus: A Bayesian network meta-analysis protocol |
title_short | Comparative efficacy and safety of traditional Chinese patent medicine for the treatment of type 2 diabetes mellitus: A Bayesian network meta-analysis protocol |
title_sort | comparative efficacy and safety of traditional chinese patent medicine for the treatment of type 2 diabetes mellitus: a bayesian network meta-analysis protocol |
topic | 3800 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7535762/ https://www.ncbi.nlm.nih.gov/pubmed/33019468 http://dx.doi.org/10.1097/MD.0000000000022564 |
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