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Construction of prediction model for gastric cancer mismatch repair based on preoperative inflammatory indicators and clinicopathological features in gastric cancer patients
Xiuzhen WEI, Yaling DONG, Zhibo ZHU, Zhengjie ZHANG, Yuanjun TAN, Jie BAI, Xiayi SU, Baihong ZHANG
PDF(713 KB)
PDF(713 KB)
Construction of prediction model for gastric cancer mismatch repair based on preoperative inflammatory indicators and clinicopathological features in gastric cancer patients
Objective To discuss the associations of mismatch repair (MMR) in gastric cancer with preoperative inflammatory indicators and clinicopathological features in the gastric cancer patients, and to construct a gastric cancer MMR predictive model based on preoperative inflammatory indicators and clinicopathological features of the gastric cancer patients, and to provide new ideas for evaluation of MMR status in gastric cancer. Methods The data of 254 gastric cancer patients who underwent surgical treatment from September 2020 to October 2023 were included. According to the expression of MMR protein, the patients were divided into MMR normal (proficiout MMR, pMMR) group and MMR deficient (dMMR) group. The preoperative inflammatory indicators and clinicopathological features data of the gastric cancer patients in two groups were collected. The associations between inflammatory indicators, clinicopathological features, and MMR in dMMR group and pMMR group were analyzed usingChi-square test. The independent predictive factors for dMMR were selected to construct the nomogram. Receiver operating characteristic (ROC) curve and calibration curve were used to evaluate the predictive efficacy, and decision curve was used to evaluate the practicality of the predication model. Results A total of 254 gastric cancer patients were included in the study, with 221 patients (87%) in pMMR group and 33 patients (13%) in dMMR group. There were statistically significant differences (P<0.05) in age, tumor location, tumor differentiation degree, maximum tumor diameter, platelet-to-lymphocyte ratio (PLR), alkaline phosphatase (AKP), alkaline phosphatase-to-albumin ratio (AAR), fibrinogen(FB)-to-lymphocyte (FLR), FB-to-albumin(AL) (FAR), D-dimer (D-D), and FB of the gastric cancer patients between dMMR group and pMMR group. Univariate and multivariate Logistic regression analysis revealed maximum tumor diameter [odd ratio(OR)=2.958, 95% confidence interval (CI):1.196-7.314, P=0.019], tumor location (OR=4.013,95%CI:1.596-10.089, P=0.003), tumor differentiation (OR=3.006, 95%CI: 1.250-7.230, P=0.014), FAR (OR=2.793, 95%CI:1.179-6.616, P=0.020), and carbohydrate antigen 199(CA199) (OR=0.279, 95%CI:0.084-0.929, P=0.038) were the independent predictors of dMMR. The area under the ROC curve (AUC) value of the gastric cancer MMR prediction model constructed based on inflammatory indicators and clinical pathological characteristics was 0.800 with the sensitivity of 0.851 and the specificity of 0.606. The calibration curve of the nomogram was found to fit the ideal curve well,and in Hosmer-Lemeshow test P=0.412, the clinical decision curve showed a better net benefit. Conclusion The preoperative inflammatory indicators and clinicopathological features are associated with MMR in gastric cancer; maximum tumor diameter, tumor location, tumor differentiation, CA199, and FAR are the independent predictors of dMMR. The prediction model based on the above predictors could predict the MMR status of the dMMR gastric cancer patients.
Stomach neoplasm / Deficient mismatch repair / Microsatellite instability / Inflammatory indicator / Prediction model
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杨军, 徐志杰, 朱卫东, 等. 微卫星不稳定性(MSI)检测技术专家共识[J]. 临床与实验病理学杂志, 2024,40(3): 228-235.
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魏秀珍和张百红参与实验的整体设计及论文撰写,董亚玲、朱志博、张政杰和谈元郡参与文献检索、数据收集及数据整理,白洁和苏夏艺参与论文的统计学分析及论文修改。
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