Objective To investigate the clinical diagnostic value of plasma RAS association domain family 1A(RASSF1A)gene methylation combined with tumor marker detection in non-small cell lung cancer(NSCLC).Methods A total of 98 NSCLC patients admitted to Qinhuangdao First Hospital from June 2023 to March 2024 were selected as the NSCLC group,and 95 patients who under-went pulmonary examinations during the same period but were not diagnosed with NSCLC were selected as the disease control group.Their general clinical data were collected.The correlations among plasma RASSF1A gene methylation,tumor markers,and clinicopatho-logical features were analyzed.The effects of RASSF1A gene methylation and tumor markers on the diagnosis of NSCLC were analyzed by the multivariate Logistic regression.A predictive model was constructed,and its effectiveness was evaluated by the receiver operating characteristics(ROC)curve and goodness of fit test.Results There were significant differences(P＜0.05)in smoking history,neu-ron specific enolase(NSE),carcinoembryonic antigen(CEA),cytokeratin 19 fragment antigen 21-1(CYFRA21-1),and RASSF1A methylation levels between the NSCLC group and non-NSCLC group.There were also significant differences(P＜0.05)in RASSF1A methylation levels,NSE,CEA,and CYFR21-1 levels among NSCLC patients with different clinical characteristics such as tumor diam-eter,differentiation degree,and growth type.The results of multivariate Logistic analysis showed that RASSF1A methylation levels(OR=1.071,95％CI:1.042-1.100),NSE(OR=1.168,95％CI:1.132-1.204),CEA(OR=1.154,95％CI:1.121-1.187),and CYFR21-1(OR=1.089,95％CI:1.023-1.195)were all independent risk factors for the diagnosis of NSCLC.A model predicting the occurrence of NSCLC was constructed using the principal component analysis(PCA)and partial least squares discriminant analysis(PLS-DA),and the ROC curve analysis results showed that the area under the ROC curve(AUCROC),sensitivity,and specificity of the prediction model for the RASSF1A methylation level combined with NSE,CEA,and CYFR21-1 were 0.922(95％CI:0.896-0.948),0.897,and 0.851,respectively,which were higher than those of the RASSF1A methylation level,NSE,CEA,and CYFR21-1 alone.Conclusion The prediction model of plasma RASSF1A gene methylation level combined with tumor markers has high diagnostic value for NSCLC and can be used for the clinical diagnosis of NSCLC.

Objective To investigate the clinical diagnostic value of plasma RAS association domain family 1A(RASSF1A)gene methylation combined with tumor marker detection in non-small cell lung cancer(NSCLC).Methods A total of 98 NSCLC patients admitted to Qinhuangdao First Hospital from June 2023 to March 2024 were selected as the NSCLC group,and 95 patients who under-went pulmonary examinations during the same period but were not diagnosed with NSCLC were selected as the disease control group.Their general clinical data were collected.The correlations among plasma RASSF1A gene methylation,tumor markers,and clinicopatho-logical features were analyzed.The effects of RASSF1A gene methylation and tumor markers on the diagnosis of NSCLC were analyzed by the multivariate Logistic regression.A predictive model was constructed,and its effectiveness was evaluated by the receiver operating characteristics(ROC)curve and goodness of fit test.Results There were significant differences(P＜0.05)in smoking history,neu-ron specific enolase(NSE),carcinoembryonic antigen(CEA),cytokeratin 19 fragment antigen 21-1(CYFRA21-1),and RASSF1A methylation levels between the NSCLC group and non-NSCLC group.There were also significant differences(P＜0.05)in RASSF1A methylation levels,NSE,CEA,and CYFR21-1 levels among NSCLC patients with different clinical characteristics such as tumor diam-eter,differentiation degree,and growth type.The results of multivariate Logistic analysis showed that RASSF1A methylation levels(OR=1.071,95％CI:1.042-1.100),NSE(OR=1.168,95％CI:1.132-1.204),CEA(OR=1.154,95％CI:1.121-1.187),and CYFR21-1(OR=1.089,95％CI:1.023-1.195)were all independent risk factors for the diagnosis of NSCLC.A model predicting the occurrence of NSCLC was constructed using the principal component analysis(PCA)and partial least squares discriminant analysis(PLS-DA),and the ROC curve analysis results showed that the area under the ROC curve(AUCROC),sensitivity,and specificity of the prediction model for the RASSF1A methylation level combined with NSE,CEA,and CYFR21-1 were 0.922(95％CI:0.896-0.948),0.897,and 0.851,respectively,which were higher than those of the RASSF1A methylation level,NSE,CEA,and CYFR21-1 alone.Conclusion The prediction model of plasma RASSF1A gene methylation level combined with tumor markers has high diagnostic value for NSCLC and can be used for the clinical diagnosis of NSCLC.