title: Discrimination analysis as a tool for classifying the value of biochemical and immunological tests in lung cancer.
abstract: The data obtained with routine biochemical, immunological and haematological tests in healthy blood donors and in patients with lung cancer were subjected to discrimination analysis with the aim to select the minimum possible combination of methods with the highest probability of distinguishing between the two groups. Transformation of lymphocytes (TR.LY) after PHA stimulation, formation of E-rosettes (E-ROS), and blood glycoproteins (GP) were shown to permit the most complete differentiation between the group of patients and the blood donors. On the basis of the above-mentioned tests the discrimination rule could be defined: IF 52,73249 - 0.45913 X E-ROS - 0.40752 X TR.LY + 0.02790 X GP greater than or equal to 0, then the investigated person is classified as a cancer patient while at values less than 0 the person is classified as a healthy individual.
mesh_terms: D003201:Computers; D006023:Glycoproteins / Q000097:blood; D006801:Humans; D008175:Lung Neoplasms / Q000175:diagnosis* / Q000276:immunology / Q000378:metabolism; D008213:Lymphocyte Activation; D010835:Phytohemagglutinins / Q000494:pharmacology; D012397:Rosette Formation; D013223:Statistics as Topic
chemical_list: D006023:Glycoproteins; D010835:Phytohemagglutinins