Global leadership initiative in malnutrition (GLIM) criteria using hand-grip strength adequately predicts postoperative complications and long-term survival in patients underwent radical gastrectomy for gastric cancer

Background: The present study aims to investigate whether malnutrition defined by the Global Leadership Initiative in Malnutrition (GLIM) criteria using hand-grip strength (HGS) adequately predict postoperative complications and long-term survival in patients underwent radical gastrectomy for gastric cancer in a similar manner to GLIM-defined malnutrition using skeletal muscle index (SMI). Methods: Patients who underwent radical gastrectomy for gastric cancer from August 2014 to June 2019 were included in this study. Clinical data were prospectively collected. Malnutrition was diagnosed based on the two-step approach following the GLIM criteria. Skeletal muscle mass was assessed using SMI based on abdominal computed tomography (CT) scans, or assessed using HGS. Results: A total of 1359 patients were included in this study, in which 36.2% of the patients were at risk of malnutrition (Nutritional Risk Screening 2002 scores ≥3). The incidence of malnutrition was 28.2% and 27.5% using SMI and HGS, respectively. There was a high agreement between the two criteria of malnutrition (kappa = 0.863, P< 0.001). Both of the two criteria of malnutrition were independently associated with postoperative complications (SMI-GLIM, P= 0.041; HGS-GLIM, P= 0.023), overall survival (P< 0.001, both), and disease-free survival (P< 0.001, both), with similar odds ratio or hazard ratio after adjusting for the same confounding variables. HGS-GLIM malnutrition (P= 0.046) but not SMI-GLIM malnutrition (P= 0.270) was associated with a higher incidence of severe complications. Conclusions: GLIM criteria using HGS is a useful tool to diagnose malnutrition and has a similar or even better predictive value for postoperative complications and long-term survival after radical gastrectomy for gastric cancer compared with GLIM criteria using SMI.