Liquid biopsy-derived multimodal models outperform CT-based evaluation for pulmonary nodule diagnosisLiquid biopsy models show better results for lung nodule diagnosis

Liquid biopsy demonstrates clinical utility as a non-invasive tool for discriminating malignant tumours from benign pulmonary nodules, as evidenced by recent research. This systematic review compared the diagnostic performance of current clinical modalities for pulmonary nodules, aiming to generate evidence-based solutions to address the underdiagnosis of malignant nodules and the overdiagnosis of benign lesions. A Bayesian bivariate random-effects model was employed to perform meta-analysis across diagnostic categories, followed by meta-regression and subgroup analyses. Results were visualised using summary receiver operating characteristic curves. Subgroup analysis revealed that liquid biopsy-derived multimodal diagnostic models achieved superior performance (sensitivity: 90.2%; specificity: 83.6%) compared to CT-based evaluation (81.5%, 67.9%) and risk prediction models (68.7%, 70.6%). These findings indicate that multimodal models integrating liquid biopsy, radiological features, and risk prediction significantly outperform single-modality approaches, thereby potentially addressing diagnostic imbalances in pulmonary nodule assessment. Key Words: Liquid biopsy, Pulmonary nodules, Multimodal diagnostic model, Comparative diagnostic test accuracy studies.