2337 - Development and Validation of a Dynamic Nomogram for Predicting Brain Metastasis in Stage III NSCLC Patients Undergoing Definitive Chemoradiotherapy
Presenter(s)
X. Chen1, X. Xiao2, M. Wang1, T. Mei3, C. Yi4, and Y. Gong5; 1Department of Thoracic Oncology and Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China, 2West China School of Basic Medical Science and Forensic Medicine, Sichuan University, Chengdu 610041, China, Chengdu, 65, China, 3Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China, 4Division of Abdominal Tumor Multimodality Treatment, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China, 5Department of Radiotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
Purpose/Objective(s): Although survival in stage III non-small cell lung cancer (NSCLC) patients receiving concurrent chemoradiotherapy (CCRT) is significantly prolonged, brain metastasis (BM) remains prevalent. This study aims to develop and validate a comprehensive model for predicting BM risk in stage III NSCLC patients, guiding personalized treatment.
Materials/Methods: A total of 311 stage III NSCLC patients who underwent CCRT were retrospectively included and divided into a training cohort (n=230) and a validation cohort (n=81). Univariate analysis identified potential predictors, followed by multivariate analysis using stepwise AIC to determine independent risk factors. A nomogram model was constructed and validated with ROC curves, calibration curves, and decision curve analysis (DCA), which was used for risk stratification.
Results: Of the 311 patients, 45 (14.5%) developed BM. Key independent predictors included sex, EGFR mutation, liver metastasis, immune maintenance deficiency, neuron-specific enolase (NSE), carcinoembryonic antigen (CEA), and absolute lymphocyte count (ALC). The nomogram showed an AUC of 0.813 and 0.775 for the training and validation sets, respectively, with favorable calibration and decision curve performance. Kaplan-Meier survival analysis showed that patients with BM had significantly shorter overall survival (43.3 vs. 75.8 months, p = 0.007). Additionally, patients receiving immune maintenance therapy after CCRT had better survival outcomes (p = 0.017). Based on a cutoff score of 393.79, patients were stratified into high- and low-risk groups, with high-risk patients demonstrating significantly worse survival (p = 0.034).
Conclusion: This study developed and validated a nomogram integrating clinical and immunologic factors to predict the risk of BM in patients with stage III NSCLC, providing a tool for early intervention in high-risk populations.