Abstract
Objective: Lung cancer patients exhibit spinal metastases from a specific population, and with this study, we aimed to develop a model that can predict this particular group's survival. Methods: Data were retrospectively collected from 83 lung cancer patients who underwent spinal metastasis surgery at our center from 2009 to 2021. After the initial assessment of treatment and scoring effects, a nomogram for survival prediction was created by identifying and integrating critical prognostic factors, followed by a consistency index (C-index) to measure consistency, and finally, a subject working characteristic curve (ROC) to compare the predictive accuracy of the three existing models. Results: The mean postoperative survival was 14.7 months. Surgical treatment significantly improved the VAS and Frankel scores in lung cancer patients with spinal metastases. The revised Tokuhashi score underestimated the life expectancy of these patients. Six independent prognostic factors, including age, extraspinal bone metastasis foci, visceral metastasis, Frankel score, targeted therapy, and radiotherapy, were identified and incorporated into the model. Calibration curves for 3-, 6-, and 12-month overall survival showed a good concordance between predicted and actual risk. The nomogram C-index for the cohort study was 0.800 (95% confidence interval [CI]: 0.757-0.843). Model comparisons showed that the nomogram's prediction accuracy was better than revised Tokuhashi and Bauer's scoring systems. Conclusions: Spine surgery offered patients the possibility of regaining neurological function. Having identified shortcomings in existing scoring systems, we have recreated and validated a new nomogram that can be used to predict survival outcomes in patients with spinal metastases from lung cancer, thereby assisting spinal surgeons in making surgical decisions and personalizing treatment for these patients.