Development of a modified nutritional index model based on nutritional status and sarcopenia to predict long-term survival and chemotherapy benefits in elderly patients with advanced gastric cancer.

[BACKGROUND] Elderly patients with advanced gastric cancer have poor prognoses. This study aims to develop a prediction model for long-term survival after radical surgery and to identify patients who may benefit from chemotherapy.

[METHODS] Data from 555 elderly patients with advanced gastric cancer admitted to two medical centers from 2009 to 2018 were retrospectively analyzed. Sarcopenia was combined with the Controlling Nutritional Status (CONUT) score to create a modified nutritional index (mCONUT). Cox regression analyses were used to develop a novel nomogram prediction model (mCNS) that combined mCONUT, pN, and tumor size, and its performance was further verified both internally and externally.

[RESULTS] Multivariate Cox analysis revealed that tumor size, pN, and mCONUT were independent prognostic risk factors for overall survival (OS). The mCNS model showed good fit and high predictive value (AUC: training set 0.711; validation set 0.707), outperforming the pTNM model (p < 0.05). To further investigate the association between the model and adjuvant chemotherapy, we categorized the model into two risk groups: a high-risk group and a low-risk group. Further analysis revealed that, in the low-risk group, the OS and recurrence-free survival(RFS) for patients receiving adjuvant chemotherapy was significantly better than that of those who did not receive chemotherapy (p = 0.047,p = 0.019). In the high-risk group, this result was not observed (p = 0.120, p = 0.053).

[CONCLUSION] The mCNS model has high predictive value in predicting long-term survival of elderly patients with advanced gastric cancer. Patients with mCNS-L were able to benefit from chemotherapy after laparoscopic radical gastrectomy.