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Comparative efficacy and safety of traditional Chinese patent medicine for endometriosis: A Bayesian network meta-analysis protocol

BACKGROUND: Endometriosis is a common disease of women of childbearing age. In recent years, the incidence of endometriosis has been on the rise. The main clinical manifestations are pelvic pain and infertility. In recent years, traditional Chinese patent medicine (TCMP) has played an important role...

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Autores principales: Dong, Shuangqian, Zhang, Jianwei, Zhai, Fengting, Zhao, Xinglong, Qin, Xiuyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6709182/
https://www.ncbi.nlm.nih.gov/pubmed/31335707
http://dx.doi.org/10.1097/MD.0000000000016473
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author Dong, Shuangqian
Zhang, Jianwei
Zhai, Fengting
Zhao, Xinglong
Qin, Xiuyun
author_facet Dong, Shuangqian
Zhang, Jianwei
Zhai, Fengting
Zhao, Xinglong
Qin, Xiuyun
author_sort Dong, Shuangqian
collection PubMed
description BACKGROUND: Endometriosis is a common disease of women of childbearing age. In recent years, the incidence of endometriosis has been on the rise. The main clinical manifestations are pelvic pain and infertility. In recent years, traditional Chinese patent medicine (TCMP) has played an important role in the treatment of endometriosis. So far, there is a lack of comparison among all the current common TCPMs for endometriosis. Consequently, it is indispensable to propose a network meta-analysis (NMA) protocol to discuss the strengths and weaknesses of different TCMPs. METHODS: We will comprehensively and systematically retrieve the relevant Chinese and English databases from their inceptions to the May 2019. All randomized controlled trials (RCTs) of TCMPs for Endometriosis will be included. Two researchers will independently screen literature, extract data and assess the risk of bias of included studies. We will conduct pairwise meta-analyses and Bayesian network meta-analyses to assess all the available evidence. Data will be analyzed using STATA and WinBUGS software. RESULTS: This work will compare and rank the relative efficacy of different TCPMs in the treatment of endometriosis in detail. CONCLUSION: The results of this study will provide reliable evidence for the selection of clinical treatment program and guideline development. PROSPERO REGISTRATION NUMBER: CRD42019127781.
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spelling pubmed-67091822019-10-01 Comparative efficacy and safety of traditional Chinese patent medicine for endometriosis: A Bayesian network meta-analysis protocol Dong, Shuangqian Zhang, Jianwei Zhai, Fengting Zhao, Xinglong Qin, Xiuyun Medicine (Baltimore) Research Article BACKGROUND: Endometriosis is a common disease of women of childbearing age. In recent years, the incidence of endometriosis has been on the rise. The main clinical manifestations are pelvic pain and infertility. In recent years, traditional Chinese patent medicine (TCMP) has played an important role in the treatment of endometriosis. So far, there is a lack of comparison among all the current common TCPMs for endometriosis. Consequently, it is indispensable to propose a network meta-analysis (NMA) protocol to discuss the strengths and weaknesses of different TCMPs. METHODS: We will comprehensively and systematically retrieve the relevant Chinese and English databases from their inceptions to the May 2019. All randomized controlled trials (RCTs) of TCMPs for Endometriosis will be included. Two researchers will independently screen literature, extract data and assess the risk of bias of included studies. We will conduct pairwise meta-analyses and Bayesian network meta-analyses to assess all the available evidence. Data will be analyzed using STATA and WinBUGS software. RESULTS: This work will compare and rank the relative efficacy of different TCPMs in the treatment of endometriosis in detail. CONCLUSION: The results of this study will provide reliable evidence for the selection of clinical treatment program and guideline development. PROSPERO REGISTRATION NUMBER: CRD42019127781. Wolters Kluwer Health 2019-07-19 /pmc/articles/PMC6709182/ /pubmed/31335707 http://dx.doi.org/10.1097/MD.0000000000016473 Text en Copyright © 2019 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 Research Article
Dong, Shuangqian
Zhang, Jianwei
Zhai, Fengting
Zhao, Xinglong
Qin, Xiuyun
Comparative efficacy and safety of traditional Chinese patent medicine for endometriosis: A Bayesian network meta-analysis protocol
title Comparative efficacy and safety of traditional Chinese patent medicine for endometriosis: A Bayesian network meta-analysis protocol
title_full Comparative efficacy and safety of traditional Chinese patent medicine for endometriosis: A Bayesian network meta-analysis protocol
title_fullStr Comparative efficacy and safety of traditional Chinese patent medicine for endometriosis: A Bayesian network meta-analysis protocol
title_full_unstemmed Comparative efficacy and safety of traditional Chinese patent medicine for endometriosis: A Bayesian network meta-analysis protocol
title_short Comparative efficacy and safety of traditional Chinese patent medicine for endometriosis: A Bayesian network meta-analysis protocol
title_sort comparative efficacy and safety of traditional chinese patent medicine for endometriosis: a bayesian network meta-analysis protocol
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6709182/
https://www.ncbi.nlm.nih.gov/pubmed/31335707
http://dx.doi.org/10.1097/MD.0000000000016473
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