Multiple markers for lung cancer diagnosis: validation of models for advanced lung cancer

Sera from 171 patients with advanced lung cancer, from 110 normals, and from 123 subjects with benign respiratory diseases were analyzed for 10 substances to detect lung cancer: ferritin, lipid-bound sialic acid, total sialic acid, beta 2-microglobulin, lipotropin, the alpha and beta subunits of human chorionic gonadotropin, calcitonin (two assays), parathyroid hormone, and carcinoembryonic antigen. Individual markers were studied, and optimal combinations of markers were sought for discriminating lung cancer patients from normals and from patients with benign lung disease. Numerous methods for combining the markers were examined, but the methods of logistic regression and recursive partitioning were finally adopted. The best discrimination rules we could find used only carcinoembryonic antigen (CEA) and total sialic acid (TSA). The performance of these rules was validated on an independent serum panel containing sera from 68 patients with advanced lung cancer, from 40 normals, and from 52 patients with benign respiratory disease. The combination rules based on TSA and CEA performed better than a rule based on CEA alone. Logistic discrimination rules with TSA and CEA that were designed to have 95% specificity achieved 54% sensitivity for discriminating advanced lung cancer from normal controls and 52% sensitivity for discriminating advanced lung cancer from controls with benign disease. Some aspects of clinical applicability are discussed, including planned studies for localized lung cancer and the requirement for further testing in specific clinical settings.