Association between GLIM-diagnosed malnutrition and quality of life in older patients with cancer

Abstract

BackgroundOlder patients with cancer have a higher risk for malnutrition and impaired quality of life (QoL). The present study aimed to investigate the relationship between malnutrition diagnosed according to the Global Leadership Initiative Malnutrition (GLIM) criteria and QoL across various tumor types, and to evaluate the combined prognostic value of malnutrition and QoL in predicting survival among older patients with cancer. MethodsThis multicenter, observational cohort study included 5310 older patients with cancer and 2184 with malnutrition (moderate stage, n = 1023; severe stage, n = 1161). An empirical cumulative distribution curve was performed to illustrate the correlation between malnutrition and QoL. The primary objective was to investigate the association between malnutrition and QoL using logistic regression analysis. Survival analyses were performed to assess the combined prognostic value of malnutrition and QoL. ResultsThe median age of the patients (66.9% male, 33.1% female) was 70 years (interquartile range [IQR] 67–74 years) years. The median QoL score was highest in patients without malnutrition (91.88 [IQR 84.44–97.44]), followed by those with moderate (86.15 [IQR 76.18–93.85) and severe (82.31 [IQR 69.87–91.11]) malnutrition. Logistics regression revealed that the risk for developing impaired QoL increased 1.98 (95% confidence interval [CI] 1.64–2.38; P < 0.001) and 2.33 (95% CI 1.93–2.81; P < 0.001) times in patients with moderate and severe malnutrition, respectively. Kaplan–Meier curves showed that QoL in combination with GLIM criteria demonstrated a significant discriminative performance for survival and served as an independent prognostic factor among older patients with cancer, especially for lung and gastric cancers. ConclusionsMalnutrition diagnosed according to the GLIM criteria was a predictor of impaired QoL. Additionally, the combination of QoL and malnutrition demonstrated utility for predicting survival outcomes in older patients with cancer.