SynthesisCancer medicine2023
The association between single nucleotide polymorphisms and ovarian cancer risk: A systematic review and network meta-analysis.
Synthesis in Cancer medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.
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Who cites it
9 citing papers in PubMed, 2 syntheses or guidelines pooled it, 14 citations in OpenAlex.
- The relationship between single nucleotide polymorphisms and skin cancer susceptibility: A systematic review and network meta-analysis.Frontiers in oncology · 2023Pooled it
- The association between single nucleotide polymorphisms and ovarian cancer risk: A systematic review and network meta-analysis.Cancer medicine · 2023Pooled it
- Role of PRKCZ non-synonymous genetic variants in breast cancer development.Cancer cell international · 2025Article
- The association of rs25487 of theBiomolecules & biomedicine · 2025Article
- Single nucleotide polymorphisms in ovarian cancer impacting lipid metabolism and prognosis: an integrated TCGA database analysis.BMC cancer · 2025Article
- Association of the Single Nucleotide Polymorphisms rs11556218, rs4778889, rs4072111, and rs1131445 of the Interleukin-16 Gene with Ovarian Cancer.International journal of molecular sciences · 2024Article
- RAD51 and Infertility: A Review and Case-Control Study.Biochemical genetics · 2024Review
- Article
- Effect of novel IL-8 gene mutation on its protein structure and stability among ovarian cancer patients in Saudi Arabia.Bioinformation · 2024Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe relationship between single nucleotide polymorphisms (SNPs) and ovarian cancer (OC) risk remains controversial. This systematic review and network meta-analysis was aimed to determine the association between SNPs and OC risk.
methodsSeveral databases (PubMed, EMBASE, China National Knowledge Infrastructure, Wanfang databases, China Science and Technology Journal Database, and China Biology Medicine disc) were searched to summarize the association between SNPs and OC published throughout April 2021. Direct meta-analysis was used to identify SNPs that could predict the incidence of OC. Ranking probability resulting from network meta-analysis and the Thakkinstian's algorithm was used to select the most appropriate gene model. The false positive report probability (FPRP) and Venice criteria were further tested for credible relationships. Subgroup analysis was also carried out to explore whether there are racial differences.
resultsA total of 63 genes and 92 SNPs were included in our study after careful consideration. Fok1 rs2228570 is likely a dominant risk factor for the development of OC compared to other selected genes. The dominant gene model of Fok1 rs2228570 (pooled OR = 1.158, 95% CI: 1.068-1.256) was determined to be the most suitable model with a FPRP <0.2 and moderate credibility.
conclusionsFok1 rs2228570 is closely linked to OC risk, and the dominant gene model is likely the most appropriate model for estimating OC susceptibility.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.