Abstract

The aim of this study was to evaluate the diagnostic value of multiple tumor marker analysis in lung cancer. Nine tumor markers, neuron-specific enolase (NSE), total sialic acid (TSA), lipid-bound sialic acid (LSA), mucinous-like carcinoma associated antigen (MCA), carbohydrate antigen 125 (CA 125), CA19-9, ferritin (FER), carcinoembriyogenic antigen (CEA) and alfa-feto protein (AFP) levels were measured in 67 patients with newly diagnosed primary lung cancer, 31 patients with benign lung diseases and 30 healthy control. Diagnostic efficacy of multiple marker combinations was evaluated with forward logistic regression (LR) analysis, and histological and stage groups were evaluated with discriminant analysis using SPSS software. In LR analysis, combination of CEA, LSA, MCA and TSA [Exp (B)=5.18, 95%CI=1.55-17.3; Exp (B)=1.37, 95%CI=1.09-1.74; Exp (B)=1.10, 95%CI=1.01-1.21; Exp (B)=1.10, 95%CI=1.04-1.16, respectively] were found to detect lung cancer in 94.9% of the cases accurately. In discriminant analysis (Wilks’ Lambda=0.68, p<0.01), NSE positivity in small cell lung cancer (SCLC) (Wilks’ Lambda=0.92, p<0.05) and FER positivity in non-SCLC (Wilks’ Lambda=0.91, p<0.05) were discriminative. The combination of these two markers were found to predict the tumor type in 77.6% of the cases accurately. In analysis of stage discrimination, there was no significant combination. Multiple tumor marker analysis can exert useful tool for disease diagnosis and prediction of histological type in primary lung cancer.