Association of PD-L1 Expression with Clinicopathologic Characters in Gastric Cancer: A Comprehensive Meta-analysis

Current Medicinal Chemistry(2024)

引用 0|浏览0
暂无评分
摘要
Purpose: The expression level of programmed death ligand-1(PD-L1) in patients with gastric cancer is the key to determining the use of immune drugs. The relationship between PD-L1 expression level and clinical characteristics is worth exploring.Methods: By setting the search terms correlated to PD-L1 and gastric cancer, a nearly comprehensive search was carried out in four major databases, and the deadline for searching was September 1, 2022. The retrieved documents were further screened by strict inclusion and exclusion criteria after removing the duplication. Next, the quality of the included studies was evaluated with the Newcastle-Ottawa Scale (NOS) scale. Finally, the STATA15.1 software was used to process data and draw plots, and the odds ratios (ORs) were adopted to assess the pooled effect size.Results: A total of 85 works of literature were included in this study through screening strictly, and detailed data were extracted after evaluating the quality of the literature. The process of analysis was conducted in the whole population, Asia-Africa population, European and American population, and Asian population with CPS >= 1, amd all found that the expression of PD-L1 in gastric cancer was correlated with age, tumor size, EBV infection, Her-2 expression and microsatellite status. However, the subgroup of the region also found some differences in Asian and Western regions, which was interesting and worth studying further. The included research of this study did not have significant publish bias.Conclusion: After careful analysis, this study found that age (>60 years), tumor size (>5cm), EBV infection (+), Her-2 expression (+), microsatellite status (MSI), and mismatch repair status (dMMR) were risk factors for positive expression of PD-L1 in gastric cancer.
更多
查看译文
关键词
PD-L1,programmed death ligand-1,B7-H1,gastric cancer,clinicopathologic characteristics
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要