Ontology highlight
ABSTRACT: 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.
SUBMITTER: Ye ZM
PROVIDER: S-EPMC7302655 | biostudies-literature | 2020 Jun
REPOSITORIES: biostudies-literature
Ye Zhuo-Miao ZM Li Li-Juan LJ Zheng Jing-Hui JH Zhang Chi C Lu Yun-Xin YX Tang Youming Y
Medicine 20200601 24
<h4>Background</h4>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.<h4>Methods</h4>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) ...[more]