Development and validation of a novel prognostic prediction system based on GLIM-defined malnutrition for colorectal cancer patients post-radical surgery - Yan, Xialin; Zhu, Junchang; Wang, Junqi; Lu, Yingjie; Ye, Xingzhao; Sun, Xiangwei; Jiang, Haojie; Li, Zongze; He, Chenhao; Zhai, Wenbo; Dong, Qiantong; Chen, Weizhe; et al. (Frontiers in Nutrition, 2024)
Background： Malnutrition often occurs in the patients with colorectal cancer. The aim of this study is to develop a predictive model based on of GLIM criteria for the patients with colorectal cancer and underwent radical surgery.Methods： From December 2015 to May 2021, patients with colorectal cancer and underwent radical surgery at our center were recruited in this study. GLIM-defined malnutrition and other clinicopathological characteristics were collected prospectively and screened by COX regeneration were applied to build the novel nomogram for prognostic prediction, which was validated and also compared with the traditional nutritional factors for prediction. Results： Among the 983 patients enrolled in this study, malnutrition was identified in 234 (23.80%) patients. Multivariate analysis indicated that GLIM-defined malnutrition is the independent risk factor for overall survival (HR=1.793, 95% CI=1.390-2.313 for moderate malnutrition and HR=3.485, 95% CI=2.087-5.818 for severe malnutrition). The novel nomogram based on GLIM criteria demonstrated a better performance than existing criteria, with AUC of 0.729, 0.703 and 0.683 for 1-year, 3-year and 5-year OS respectively in validation cohort. Besides, the risk score determined by this system exhibited the significantly poorer short-term and long-term clinical outcomes in high-risk group in both malnourished and well-nourished patients.Conclusion： Combining with handgrip strength, serum albumin level, TNM stage and etc. would improve the predictive effect of GLIM criteria for the patients with colorectal cancer who underwent radical surgery, and benefit the individual prognostic prediction of colorectal cancer.