ArticleMedicine2020
A comprehensive evaluation of single nucleotide polymorphisms associated with gastric cancer risk: A protocol for systematic review and network meta-analysis.
Article in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Hotspots and trends of risk factors in gastric cancer: A visualization and bibliometric analysis.World journal of gastrointestinal oncology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSingle nucleotide polymorphisms (SNPs) have been inconsistently associated with gastric cancer (GC) risk. This meta-analysis aimed to synthesize relevant data on SNPs associated with GC.
methodsDatabases were searched to identify association studies of SNPs and GC 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, and Wan fang databases. Network meta-analysis and Thakkinstian algorithm were used to select the most appropriate genetic model, along with false positive report probability for noteworthy associations. The methodological quality of data was assessed based on the STrengthening the REporting of Genetic Association Studies statement Stata 14.0 will be used for systematic review and meta-analysis.
resultsThis study will provide a high-quality evidence to find the SNP most associated with GC susceptibility and the best genetic model.
conclusionsThis study will explore which SNP is most associated with GC susceptibility. REGISTRATION: INPLASY202040132.
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