Pulmonary nodules: A study on combined diagnostic methods and therapeutic evaluation

Lung cancer remains a leading cause of cancer-related mortality globally, with pulmonary nodules critical for early detection and risk stratification. While low-dose spiral computed tomography (LDCT) has improved screening, its high sensitivity demands more accurate triage to reduce unnecessary invasive procedures. This study evaluated combining blood-based biomarkers—traditional tumor markers, cell-free DNA (cfDNA) methylation, and seven tumor-associated autoantibodies (7-AABs)—for identifying high-risk nodules and assessing treatment response. A total of 141 lung cancer patients with pulmonary nodules and 82 with benign nodules were enrolled. All underwent preoperative detection of traditional markers (CEA, VEGF, etc.), cfDNA methylation (SHOX2, RASSF1A, PTGER4), and 7-AABs (p53, SOX2, etc.). Lung cancer patients also had postoperative and post-chemotherapy assessments of cfDNA methylation and 7-AABs. Imaging features (size, morphology) were evaluated, with analyses including chi-square tests, logistic regression, and ROC curves. Results showed cfDNA methylation had the highest diagnostic efficacy (sensitivity: 78.0 %, specificity: 76.8 %, AUC: 0.7743), followed by 7-AABs (43.3 % sensitivity, 87.8 % specificity, AUC: 0.6553). Traditional markers were less useful (highest AUC: 0.5768 for SCC). Logistic regression identified high-risk morphology (OR = 2.676), positive cfDNA methylation (OR = 15.733), and positive 7-AABs (OR = 3.821) as independent malignancy predictors. Both biomarkers decreased postoperatively, with cfDNA methylation further declining after chemotherapy, suggesting utility for minimal residual disease monitoring. This study demonstrates combining imaging with cfDNA methylation and 7-AABs enhances preoperative risk stratification. These biomarkers also show promise for evaluating treatment response and guiding surveillance, supporting their use in precise lung cancer management.