Construction of prediction model for gastric cancer mismatch repair based on preoperative inflammatory indicators and clinicopathological features in gastric cancer patients
10.13481/j.1671-587X.20250121
- VernacularTitle:基于胃癌患者术前炎性指标和临床病理特征的胃癌错配修复预测模型的构建
- Author:
Xiuzhen WEI
1
;
Yaling DONG
;
Zhibo ZHU
;
Zhengjie ZHANG
;
Yuanjun TAN
;
Jie BAI
;
Xiayi SU
;
Baihong ZHANG
Author Information
1. 甘肃中医药大学第一临床医学院,甘肃兰州 730030;中国人民解放军联勤保障部队第九四○医院肿瘤科,甘肃兰州 730050;甘肃省武威市凉州医院消化内科,甘肃武威 733000
- Keywords:
Stomach neoplasm;
Deficient mismatch repair;
Microsatellite instability;
Inflammatory indicator;
Prediction model
- From:
Journal of Jilin University(Medicine Edition)
2025;51(1):172-181
- CountryChina
- Language:Chinese
-
Abstract:
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 using Chi-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.
