Abstract
BACKGROUND: Efficient early detection methods for lung cancer can significantly decrease patient mortality. One promising approach is the use of tumor-associated autoantibodies (TAABs) as a diagnostic tool. In this study, the researchers aimed to evaluate the potential of seven TAABs in detecting lung cancer within a population undergoing routine health examinations. The results of this study could provide valuable insights into the utility of TAABs for lung cancer screening and diagnosis. METHODS: In this study, the serum concentrations of specific antibodies were measured using enzyme-linked immunosorbent assay (ELISA) in a cohort of 15,430 subjects. The efficacy of both a 7-TAAB panel and LDCT for lung cancer detection were evaluated through receiver operating characteristic (ROC) analyses, with sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) being assessed and compared. These results could have significant implications for the development of improved screening methods for lung cancer. RESULTS: Over the 12-month observation period, 26 individuals were diagnosed with lung cancer. The 7-TAAB panel demonstrated promising sensitivity (61.5%) and a high degree of specificity (88.5%). The panel's area under the receiver operating characteristic (ROC) curve was 0.8062, which was superior to that of any individual TAAB. In stage I patients, the sensitivity of the panel was 50%. In our cohort, there was no gender or age bias observed. This 7-TAAB panel showed a sensitivity of approximately 60% in detecting lung cancer, regardless of histological subtype or lesion size. Notably, ground-glass nodules had a higher diagnostic rate than solid nodules (83.3% vs. 36.4%, P = 0.021). The ROC analyses further revealed that the combination of LDCT with the 7-TAAB assay exhibited a significantly superior diagnostic efficacy than LDCT alone. CONCLUSION: In the context of the study, it was demonstrated that the 7-TAAB panel showed improved detective efficacy of LDCT, thus serving as an effective aid for the detection of lung cancer in real-world scenarios.