Application of autoantibody binding curve characteristics and machine learning methods for improving the diagnostic performance of an early detection test for lung cancer - Allen, Jared (2023)
The EarlyCDT®-Lung test has been technically and clinically validated for the early detection of lung cancer with a sensitivity ~40% and a specificity of ~90% through measurement of a panel of seven serum autoantibodies. The test generates curves of autoantibody binding to a titrated series of capture antigen concentrations thus providing patient-specific autoantibody profile titration curves. We postulated that the antibodies responsible for false positive results in healthy individuals exhibit different binding kinetics to specific autoantibodies present in cancer patients and that these differences may manifest themselves in the shape of the autoantibody-antigen titration curves.