Muscle-Related Parameters as Determinants of Survival in Patients with Stage I-III Gastric Cancer Undergoing Gastrectomy

Purpose: This study aimed to evaluate the prognostic potential of muscle-related parameters (MRPs) at the level of the third lumbar vertebra (L3) using computerized tomography (CT) images in patients with stage I-III gastric cancer (GC) who underwent curative gastric resection. Methods: Patients with stage I-III GC who underwent curative gastric resection between October 2006 and June 2014 were enrolled in this study. In addition to demographic and clinical parameters, MRPs, such as skeletal muscle index (SMI), skeletal muscle radiation attenuation (SMRA), paraspinal muscle index (PMI), and paraspinal muscle radiation attenuation (PMRA), at the L3 level using CT images were collected and analyzed. The Kaplan-Meier method was used to estimate survival, and a Cox proportional hazard model was used to calculate the hazard ratio. In addition, the Pearson correlation coefficient was obtained as a measure of the linear relationship between the variables. Results: Data from 339 patients (233 men and 116 women) were analyzed. A strong correlation between SMI and PMI (r = 0.91); and SMRA and PMRA (r = 0.80) were observed, but only weak correlations between SMI and SMRA; and PMI and PMRA were found. When using the Cox model, SMRA or PMRA was a determinant of survival, but SMI and PMI were not. In the full model formed by adding SMRA or PMRA to a baseline model that included demographic and clinical variables, the C-index increased above 0.8, indicating excellent discrimination for both overall survival (OS) and disease-free survival (DFS). Moreover, the C-index of the model containing PMRA was higher than that of the model containing SMRA. Finally, there was a weak correlation between the prognostic nutritional index and SMRA or PMRA. Conclusions: With the multivariate Cox model, SMRA and PMRA appeared to determine survival. In addition, adding SMRA or PMRA to the baseline model increased the C-index above 0.8, indicating excellent discrimination for both OS and DFS. Moreover, compared to SMRA, the model containing PMRA appears to be a more accurate model for survival determination.