Predicting the risk of sarcopenia in Nasopharyngeal Carcinoma patients: Development and assessment of a new predictive nomogram

Abstract Purpose Sarcopenia, as defined by the Global Leadership Initiative on Malnutrition (GLIM) consensus, serves as a diagnostic indicator for malnutrition and has been shown to influence cancer treatment and clinical results. However, the impact of sarcopenia on individuals diagnosed with nasopharyngeal carcinoma (NPC) remain insufficiently elucidated. The objective of this study was to investigate the prognostic significance of sarcopenia on the survival outcomes of NPC patients and to develop a nomogram. Patients and methods: 545 patients with stage III-IVa NPC were included in this retrospective study and randomly divided into training and validation cohort (381 and 164 patients, respectively). Sarcopenia was defined using the skeletal muscle index (SMI) determined at the C3 level based on baseline MRI. The nomogram was developed utilizing a multivariable Cox model with baseline variables from the training cohort, and validated with the validation cohort. The nomogram's discriminative ability and accuracy were evaluated using the consistency index (C-index), receiver operating characteristic curve (ROC), and calibration plots, while the net benefit was assessed and compared with the TNM clinical stage through decision curve analysis (DCA). Results The results of the multivariate analysis revealed that higher T stage (HR = 2.15, 95% CI: 1.3–3.57, P < 0.01), higher N stage (HR = 2.15, 95% CI: 1.56–2.95, P < 0.01), sarcopenia group (HR = 2.46, 95% CI: 1.58–3.83, P < 0.01), and a history of comorbidities (HR = 1.76, 95% CI: 1.16–2.67, P = 0.01) were identified as independent risk factors that significantly impacted both overall survival (OS). The C-index (0.731 for the training cohort and 0.72 for the validation cohort indicated satisfactory discriminative ability of the nomogram. The calibration plots showed favorable consistency between the prediction of the nomogram and actual observations in both the training and validation cohorts. Moreover, nomograms also showed higher outcomes of DCA and the area under the curve (AUC) compared to TNM clinical stage. Conclusion Sarcopenia, T stage, N stage, and comorbidities were identified as independent prognostic factors for locally advanced NPC (laNPC). The integration of these factors into a nomogram predictive model demonstrated enhanced predictive accuracy.