The optimal combination of serum tumor markers with bioinformatics in diagnosis of colorectal carcinoma

Objective: To identify the optimal combination of serum tumor markers with bioinformatics in diagnosis of colorectal cancer. Methods: The serum levels of CEA, AFP, NSE, CA199, CA242, CA724, CA211 and TPA were detected in 128 patients with colorectal carcinoma and 113 health subjects. The serum tumor markers were evaluated with the area under curves. The optimal combination of serum tumor markers was selected and the diagnostic model with artificial neural network was established. Results: CEA,CA199,CA242,CA211,CA724 were selected for the optimal combination and the artificial neural network was built. The model was evaluated by a 5 cross validation approach. The model had a specificity of 95%, sensitivity of 83% and positive predictive value of 95% in diagnosis of colorectal carcinoma. Conclusion: The combination of optimal serum tumor markers has a high sensitivity and specificity in diagnosis of colorectal carcinoma.