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Complementary and alternative therapies for precancerous lesions of gastric cancer: A protocol for a Bayesian network meta analysis
BACKGROUND: Gastric cancer is one of the most common malignant tumors, which seriously affect peoples quality of life and threaten people's health. Precancerous lesions of gastric cancer (PLGC) are a critical stage in the occurrence and development of gastric cancer. Early effective interventio...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7808479/ https://www.ncbi.nlm.nih.gov/pubmed/33466209 http://dx.doi.org/10.1097/MD.0000000000024249 |
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author | Zhang, Tianqi Zhang, Tiefeng Li, Chuancheng Zhai, Xixi Huo, Qing |
author_facet | Zhang, Tianqi Zhang, Tiefeng Li, Chuancheng Zhai, Xixi Huo, Qing |
author_sort | Zhang, Tianqi |
collection | PubMed |
description | BACKGROUND: Gastric cancer is one of the most common malignant tumors, which seriously affect peoples quality of life and threaten people's health. Precancerous lesions of gastric cancer (PLGC) are a critical stage in the occurrence and development of gastric cancer. Early effective intervention is an important means to prevent and control gastric cancer. In this study, we will evaluate the efficacy and safety of complementary and alternative therapies in the treatment of PLGC by Bayesian network meta-analysis (NMA). METHODS: We will search PubMed, Cochrane Library, CNKI and other databases to gather randomized controlled trials (RCTs) on the treatment of PLGC with complementary and alternative therapies. Two reviewers will screen the literature and extract the data according to the inclusion and exclusion criteria, and then assess the quality and bias risk according to Cochrane's Risk of Bias Assessment Tool. Bayesian network meta-analysis will be conducted by Stata16.0 and WinBUGS1.4.3. RESULTS: This study will compare and rank the efficacy and safety of different complementary and alternative therapies for PLGC. CONCLUSION: This study can provide reliable evidence for the efficacy and safety of complementary and alternative therapies in treatment of PLGC. We expect to provide scientific and rigorous evidence support for clinicians and patients, and then assist them to choose the optimum treatment. PROTOCOL REGISTRATION NUMBER: INPLASY2020120077. |
format | Online Article Text |
id | pubmed-7808479 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-78084792021-01-15 Complementary and alternative therapies for precancerous lesions of gastric cancer: A protocol for a Bayesian network meta analysis Zhang, Tianqi Zhang, Tiefeng Li, Chuancheng Zhai, Xixi Huo, Qing Medicine (Baltimore) 3800 BACKGROUND: Gastric cancer is one of the most common malignant tumors, which seriously affect peoples quality of life and threaten people's health. Precancerous lesions of gastric cancer (PLGC) are a critical stage in the occurrence and development of gastric cancer. Early effective intervention is an important means to prevent and control gastric cancer. In this study, we will evaluate the efficacy and safety of complementary and alternative therapies in the treatment of PLGC by Bayesian network meta-analysis (NMA). METHODS: We will search PubMed, Cochrane Library, CNKI and other databases to gather randomized controlled trials (RCTs) on the treatment of PLGC with complementary and alternative therapies. Two reviewers will screen the literature and extract the data according to the inclusion and exclusion criteria, and then assess the quality and bias risk according to Cochrane's Risk of Bias Assessment Tool. Bayesian network meta-analysis will be conducted by Stata16.0 and WinBUGS1.4.3. RESULTS: This study will compare and rank the efficacy and safety of different complementary and alternative therapies for PLGC. CONCLUSION: This study can provide reliable evidence for the efficacy and safety of complementary and alternative therapies in treatment of PLGC. We expect to provide scientific and rigorous evidence support for clinicians and patients, and then assist them to choose the optimum treatment. PROTOCOL REGISTRATION NUMBER: INPLASY2020120077. Lippincott Williams & Wilkins 2021-01-15 /pmc/articles/PMC7808479/ /pubmed/33466209 http://dx.doi.org/10.1097/MD.0000000000024249 Text en Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc. https://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 (https://creativecommons.org/licenses/by/4.0/) |
spellingShingle | 3800 Zhang, Tianqi Zhang, Tiefeng Li, Chuancheng Zhai, Xixi Huo, Qing Complementary and alternative therapies for precancerous lesions of gastric cancer: A protocol for a Bayesian network meta analysis |
title | Complementary and alternative therapies for precancerous lesions of gastric cancer: A protocol for a Bayesian network meta analysis |
title_full | Complementary and alternative therapies for precancerous lesions of gastric cancer: A protocol for a Bayesian network meta analysis |
title_fullStr | Complementary and alternative therapies for precancerous lesions of gastric cancer: A protocol for a Bayesian network meta analysis |
title_full_unstemmed | Complementary and alternative therapies for precancerous lesions of gastric cancer: A protocol for a Bayesian network meta analysis |
title_short | Complementary and alternative therapies for precancerous lesions of gastric cancer: A protocol for a Bayesian network meta analysis |
title_sort | complementary and alternative therapies for precancerous lesions of gastric cancer: a protocol for a bayesian network meta analysis |
topic | 3800 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7808479/ https://www.ncbi.nlm.nih.gov/pubmed/33466209 http://dx.doi.org/10.1097/MD.0000000000024249 |
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