Malnutrition defined by three global leadership initiative on malnutrition‐based models and the risk of all‐cause mortality in adults with common cancers: A retrospective cohort study

Objective Our study compared the diagnostic agreement and prognostic value for overall survival of three nutritional screening tools integrated with the Global Leadership Initiative on Malnutrition framework in patients with cancer. Methods The nutritional screening tools evaluated were the Malnutrition Universal Screening Tool, Malnutrition Screening Tool, and Nutritional Risk Screening 2002. Prognostic assessment was conducted using Kaplan‐Meier survival analysis and Cox proportional hazards regression, with sensitivity analyses to ensure robustness. Logistic regression analysis was employed to assess the predictive value of each Global Leadership Initiative on Malnutrition‐based model for malnutrition. Harrell's concordance index compared the discriminatory power of the models for overall survival outcomes, while kappa statistics evaluated diagnostic consistency for malnutrition across the models. Results Each of the three models combining the Global Leadership Initiative on Malnutrition criteria with the Malnutrition Universal Screening Tool, the Malnutrition Screening Tool, or Nutritional Risk Screening 2002 was independently associated with an increased risk of all‐cause mortality. The corresponding hazard ratios were 1.494, 1.517, and 1.530, respectively, with all P values less than 0.001. Across all three models, mortality risk increased progressively with the severity of malnutrition, while their discriminatory performance for overall survival was comparable. Among the three models, the model incorporating the Malnutrition Screening Tool demonstrated the strongest agreement with the Patient‐Generated Subjective Global Assessment (kappa = 0.481, P < 0.001) and the greatest ability to identify malnutrition. Conclusions All three models provided meaningful prognostic information. The model incorporating the Malnutrition Screening Tool showed the closest diagnostic agreement and the strongest identification of clinically significant malnutrition.