Prognostic utility of the global leadership initiative on malnutrition criteria in predicting outcomes after hepatectomy for hepatocellular carcinoma: a multicenter, retrospective study - Liang, Yaohao; Lu, Zhan; Ruan, Tianyu; Wu, Shanglin; Meng, Jianyi; Jiang, Jie; He, Jiaqian; Jiang, Liyan; Tan, Ning; Tan, Shengqiang (Frontiers in Nutrition, 2025)
ObjectiveThe Global Leadership Initiative on Malnutrition (GLIM) criteria were developed to standardize diagnoses of malnutrition. However, the prognostic utility of the GLIM criteria and predictive models including GLIM criteria in patients diagnosed with hepatocellular carcinoma (HCC) undergoing hepatectomy remains largely unexplored.MethodsThis retrospective study included 477 HCC patients who underwent curative hepatectomy at two centers (training cohort: n = 297, January 2014 to November 2020; validation cohort: n = 180, April 2018 to December 2019). A nomogram was developed using multivariate Cox regression analysis. The utility of the developed model was evaluated by Harrell concordance index (C-index), calibration curve, and decision curve analysis (DCA). Time-dependent receiver operating characteristic (ROC) curves and DCA were used to compare the nomogram with existing prognostic models.ResultsThe prevalence of malnutrition was 30.6 and 25.6% in the training and validation cohorts, respectively. Non-malnourished patients exhibited superior overall survival (OS) across all BCLC stages (p < 0.001). Multivariate analysis identified GLIM-diagnosed malnutrition, albumin <35 g/L, tumor size >5 cm, alpha-fetoprotein (AFP) ≥400 ng/mL, and tumor number ≥3 as independent predictors of OS. The nomogram for 3-year OS achieved C-indices of 0.735 and 0.666 in the training and validation cohorts, respectively. External validation demonstrated good discrimination and calibration. The nomogram outperformed the ALBI, PNI, and BCLC staging systems in terms of AUC and DCA.ConclusionGLIM-diagnosed malnutrition was an independent risk factor for OS in patients with HCC undergoing hepatectomy. The nomogram including GLIM is a good tool for predicting postoperative OS in this patient population.