The spine is a common site for metastases in lung cancer. Precise identification of factors associated with survival and reliable prediction of prognosis are essential for clinical decision-making in patients with spinal metastasis from lung cancer. A retrospective analysis was conducted on 148 lung cancer patients with spinal metastases between January 2018 and December 2020 to identify prognostic factors and develop a nomogram for predicting survival outcomes. Another 30 patients with spinal metastases due to lung cancer, treated between January 2021 and February 2022, served as an external validation cohort to assess the nomogram's predictive performance. Multivariate analysis identified Karnofsky Performance Status (KPS) score, carbohydrate antigen 125 (CA125), radiotherapy, chemotherapy, and targeted therapy as independent prognostic factors. The nomogram achieved a concordance index of 0.713. The AUCs for the nomogram in predicting 1-, 2-, and 3-year survival were 0.834, 0.750, and 0.733 in the training set; 0.803, 0.738, and 0.713 in the internal validation set; and 0.749, 0.738, and 0.729 in the external validation set. Calibration curves showed good agreement between predicted and observed outcomes. Compared with the modified Tokuhashi and Tomita scores, the nomogram demonstrated superior predictive accuracy and provided greater net clinical benefit in decision curve analysis, indicating good clinical utility. This model may aid individualized prognosis assessment and treatment planning in lung cancer patients with spinal metastases.
Keywords: Lung cancer; predictive model; prognostic factors; spinal metastases; survival analysis.
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