The association between single nucleotide polymorphisms and ovarian cancer risk: A systematic review and network meta‐analysis

BACKGROUND: The 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. METHODS: Several 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. RESULTS: A 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. CONCLUSIONS: Fok1 rs2228570 is closely linked to OC risk, and the dominant gene model is likely the most appropriate model for estimating OC susceptibility.