Abstract
PURPOSE: The objective is to establish a radiomics nomogram (Rad-nomogram) using dual-phase enhanced computed tomography (DPE-CT) for the prediction of progression-free survival (PFS) in patients diagnosed with stage IV lung adenocarcinoma (ADC). METHODS: From DPE-CT scans, radiomic characteristics were retrieved from 133 patients diagnosed with stage IV lung ADC. Clinical data were analyzed using univariate and multivariate Cox regression analyses. The radiomics signature was combined with clinical features employing multivariate Cox analysis in order to develop a Rad-nomogram. The predictive efficiency of the nomogram was evaluated using survival studies, such as Kaplan-Meier curves and Harrell's C-index. The benefits and clinical utility of various models were compared using the net reclassification index (NRI), decision curve analysis (DCA), and integrated discrimination improvement (IDI). RESULTS: In the test cohort, the C-indexes for the clinical, artery, and vein phase CT models were 0.675, 0.691, and 0.678, respectively. The dual-phase achieved a C-index of 0.731, exceeding the CT model, while the developed nomogram reached a C-index of 0.783. The Kaplan-Meier survival study classified patients into low-risk and high-risk groups related to PFS using the Rad-nomogram (p < 0.05). The Rad-nomogram demonstrated a greater net advantage when compared with clinical and Rad models, as indicated by positive values of the NRI and IDI (ranging from 11.6% to 52.6%, p < 0.05). CONCLUSION: The Rad-nomogram, employing DPE-CT scans, offers a promising approach to predict PFS in individuals diagnosed with stage IV lung ADC.