Wei-Qiong Ni, Fei Xu, Yu-Ling Zhang, Yong-Miao Lin, Xin Huang, Wen Xia, Nan-Jun Chen, Qin-Wen Du, Chen Ren, Sha-Sha Du, Xin Hua
A prognostic model combining GNRI, sarcopenia, and clinicopathological factors effectively stratifies risk in NPC patients receiving CCRT. This integrated approach improves upon conventional staging in predicting OS and supports incorporating comprehensive nutritional and body composition assessments into routine clinical practice to guide personalized treatment strategies.
BACKGROUND: Nasopharyngeal carcinoma (NPC) is a heterogeneous malignancy with significant variability in survival outcomes among patients receiving concurrent chemoradiotherapy (CCRT), even within the same disease stage. This study aimed to develop and validate a novel prognostic model integrating the geriatric nutritional risk index (GNRI) and sarcopenia to predict overall survival (OS) in NPC patients undergoing CCRT.
METHODS: We conducted a large-scale, long-term retrospective analysis of 862 NPC patients treated with CCRT. Pretreatment GNRI and sarcopenia status were assessed, and patients were stratified into cachexia risk groups based on these two factors. Univariate and multivariate Cox regression analyses identified independent prognostic predictors, which were incorporated into a nomogram for individualized OS prediction.
RESULTS: Patients classified as high cachexia risk (low GNRI or presence of sarcopenia) exhibited significantly poorer OS compared to the low cachexia risk group (HR = 0.607, 95% CI: 0.428-0.861, P = 0.005). Multivariate analysis revealed that age > 45 years, advanced T stage, nodal involvement, and high cachexia risk independently predicted worse OS. The nomogram demonstrated favorable discrimination (C-index = 0.715, 95% CI: 0.643-0.787) compared to the traditional tumor-node-metastasis (TNM) staging system (C-index = 0.639, 95% CI: 0.574-0.704).
CONCLUSIONS: A prognostic model combining GNRI, sarcopenia, and clinicopathological factors effectively stratifies risk in NPC patients receiving CCRT. This integrated approach improves upon conventional staging in predicting OS and supports incorporating comprehensive nutritional and body composition assessments into routine clinical practice to guide personalized treatment strategies.