Comparison of laparoscopic surgery with open standard surgery for advanced gastric carcinoma in a single institute: a propensity score matching analysis

A meta-analysis of the effect of laparoscopic gastric resection on the surgical site wound infection in patients with advanced gastric cancer

By conducting a meta-analysis of relevant clinical studies on the treatment of advanced gastric cancer (GC) using laparoscopic and open surgeries, we aimed to evaluate the impact of these two surgical approaches on postoperative surgical site infections (SSIs) in patients with advanced GC. We aimed to provide evidence-based support for preventing SSIs in postoperative patients with advanced GC. From database establishment until May 2023, we systematically searched PubMed, Cochrane Library, MEDLINE, Embase, China National Knowledge Infrastructure, and Wanfang Data databases for relevant studies comparing laparoscopic and open surgeries for the treatment of advanced GC. Two researchers independently performed the literature screening and data extraction based on predefined inclusion and exclusion criteria. The meta-analysis was conducted using STATA 17.0. Twenty articles involving 3084 patients met the inclusion criteria, including 1462 patients in the laparoscopic group and 1622 cases in the open surgery group. The meta-analysis results revealed that the incidence of postoperative SSIs was significantly lower in the laparoscopic group than in the open surgery group (odds ratio = 0.341, 95% confidence interval: 0.219-0.532, p < 0.001). The current evidence indicates that laparoscopic radical gastrectomy can significantly reduce the incidence of postoperative site infections in patients with advanced GC.

Establishment and Systematic Evaluation of Gastric Cancer Classification Model Based on Pyroptosis

Background: Gastric cancer (GC) is considered the fifth most prevalent type of cancer and the third leading cause of cancer deaths worldwide. This in-depth investigation was performed to generate fresh concepts for the clinical classification, diagnosis, and prognostic evaluation of GC. Methods: The data were retrieved from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Unsupervised cluster analysis was used to divide up the GC patients using pyroptosis-related differentially expressed genes (DEGs), which were discovered to be significantly linked with GC prognosis. The therapeutic importance of pyroptosis in GC patients was discovered using PCA analysis of genes associated with pyroptosis. The models were then carefully scrutinized. Results: Three hub genes, ELANE, IL6, and TIRAP, exhibit significant predictive importance among the 15 pyroptosis-related genes. Unsupervised clustering analysis revealed that the DEGs were enriched in the pathway of cytokine-cytokine receptor interactions, and Clusters 1 and 2 had statistically distinct prognoses. PCA analysis revealed significant differences in the area under the curve, immunological checkpoints, immunogenic cell death, and prognostic value between the high- and low-risk groups. Conclusions: These two GC classification models, based on pyroptosis, have significant clinical value for patients with GC.