Department of Gastroenterology, The Second Xiangya Hospital, Central South University, Changsha, China.
Research Center of Digestive Disease, The Second Xiangya Hospital, Central South University, Changsha, China.
Cancer Med. 2023 Jan;12(1):541-556. doi: 10.1002/cam4.4891. Epub 2022 May 30.
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.
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.
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.
Fok1 rs2228570 is closely linked to OC risk, and the dominant gene model is likely the most appropriate model for estimating OC susceptibility.
单核苷酸多态性（SNP）与卵巢癌（OC）风险之间的关系仍存在争议。本系统评价和网络荟萃分析旨在确定 SNP 与 OC 风险之间的关联。
检索了多个数据库（PubMed、EMBASE、中国知网、万方数据库、中国科技期刊数据库和中国生物医学文献数据库），以总结截至 2021 年 4 月发表的 SNP 与 OC 相关的研究。直接荟萃分析用于确定可预测 OC 发生率的 SNP。网络荟萃分析和 Thakkinstian 算法的排序概率用于选择最合适的基因模型。进一步使用虚假阳性报告概率（FPRP）和威尼斯标准对可信关系进行测试。还进行了亚组分析，以探讨是否存在种族差异。
经过仔细考虑，本研究共纳入 63 个基因和 92 个 SNP。与其他选定基因相比，Fok1 rs2228570 可能是 OC 发展的显性危险因素。Fok1 rs2228570 的显性基因模型（合并 OR=1.158，95%CI：1.068-1.256）被确定为最适合的模型，FPRP<0.2，可信度适中。
Fok1 rs2228570 与 OC 风险密切相关，显性基因模型可能是估计 OC 易感性的最合适模型。
