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A comprehensive assessment of single nucleotide polymorphisms associated with pancreatic cancer risk: A protocol for systematic review and network meta-analysis
BACKGROUND: Single nucleotide polymorphisms (SNPs) have been inconsistently associated with pancreatic cancer (PC) risk. This meta-analysis aimed to synthesize relevant data on SNPs associated with PC. METHODS: Databases were searched to identify association studies of SNPs and PC published through...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7302655/ https://www.ncbi.nlm.nih.gov/pubmed/32541456 http://dx.doi.org/10.1097/MD.0000000000020345 |
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author | Ye, Zhuo-Miao Li, Li-Juan Zheng, Jing-Hui Zhang, Chi Lu, Yun-Xin Tang, Youming |
author_facet | Ye, Zhuo-Miao Li, Li-Juan Zheng, Jing-Hui Zhang, Chi Lu, Yun-Xin Tang, Youming |
author_sort | Ye, Zhuo-Miao |
collection | PubMed |
description | BACKGROUND: Single nucleotide polymorphisms (SNPs) have been inconsistently associated with pancreatic cancer (PC) risk. This meta-analysis aimed to synthesize relevant data on SNPs associated with PC. METHODS: Databases were searched to identify association studies of SNPs and PC published through January 2020 from the databases of PubMed, Web of Science, Embase, Cochrane Library, China National Knowledge Infrastructure, the Chinese Science and Technology Periodical Database (VIP) and Wanfang databases. Network meta-analysis and Thakkinstian algorithm were used to select the most appropriate genetic model, along with false positive report probability (FPRP) for noteworthy associations. The methodological quality of data was assessed based on the STREGA statement Stata 14.0 will be used for systematic review and meta-analysis. RESULTS: This study will provide a high-quality evidence to find the SNP most associated with pancreatic cancer susceptibility and the best genetic model. CONCLUSIONS: This study will explore which SNP is most associated with pancreatic cancer susceptibility. Registration: INPLASY202040023. |
format | Online Article Text |
id | pubmed-7302655 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Wolters Kluwer Health |
record_format | MEDLINE/PubMed |
spelling | pubmed-73026552020-06-29 A comprehensive assessment of single nucleotide polymorphisms associated with pancreatic cancer risk: A protocol for systematic review and network meta-analysis Ye, Zhuo-Miao Li, Li-Juan Zheng, Jing-Hui Zhang, Chi Lu, Yun-Xin Tang, Youming Medicine (Baltimore) 5700 BACKGROUND: Single nucleotide polymorphisms (SNPs) have been inconsistently associated with pancreatic cancer (PC) risk. This meta-analysis aimed to synthesize relevant data on SNPs associated with PC. METHODS: Databases were searched to identify association studies of SNPs and PC published through January 2020 from the databases of PubMed, Web of Science, Embase, Cochrane Library, China National Knowledge Infrastructure, the Chinese Science and Technology Periodical Database (VIP) and Wanfang databases. Network meta-analysis and Thakkinstian algorithm were used to select the most appropriate genetic model, along with false positive report probability (FPRP) for noteworthy associations. The methodological quality of data was assessed based on the STREGA statement Stata 14.0 will be used for systematic review and meta-analysis. RESULTS: This study will provide a high-quality evidence to find the SNP most associated with pancreatic cancer susceptibility and the best genetic model. CONCLUSIONS: This study will explore which SNP is most associated with pancreatic cancer susceptibility. Registration: INPLASY202040023. Wolters Kluwer Health 2020-06-12 /pmc/articles/PMC7302655/ /pubmed/32541456 http://dx.doi.org/10.1097/MD.0000000000020345 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 | 5700 Ye, Zhuo-Miao Li, Li-Juan Zheng, Jing-Hui Zhang, Chi Lu, Yun-Xin Tang, Youming A comprehensive assessment of single nucleotide polymorphisms associated with pancreatic cancer risk: A protocol for systematic review and network meta-analysis |
title | A comprehensive assessment of single nucleotide polymorphisms associated with pancreatic cancer risk: A protocol for systematic review and network meta-analysis |
title_full | A comprehensive assessment of single nucleotide polymorphisms associated with pancreatic cancer risk: A protocol for systematic review and network meta-analysis |
title_fullStr | A comprehensive assessment of single nucleotide polymorphisms associated with pancreatic cancer risk: A protocol for systematic review and network meta-analysis |
title_full_unstemmed | A comprehensive assessment of single nucleotide polymorphisms associated with pancreatic cancer risk: A protocol for systematic review and network meta-analysis |
title_short | A comprehensive assessment of single nucleotide polymorphisms associated with pancreatic cancer risk: A protocol for systematic review and network meta-analysis |
title_sort | comprehensive assessment of single nucleotide polymorphisms associated with pancreatic cancer risk: a protocol for systematic review and network meta-analysis |
topic | 5700 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7302655/ https://www.ncbi.nlm.nih.gov/pubmed/32541456 http://dx.doi.org/10.1097/MD.0000000000020345 |
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