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Background & aims: Elderly cancer patients are at particularly high risk for malnutrition because both the disease and the old age threaten their nutritional status. The Global Leadership Initiative on Malnutrition (GLIM) released new universal criteria for diagnosing and grading malnutrition, but the validation of these criteria in elderly cancer population is not well documented. Our objective was to investigate the application of the GLIM criteria in nutrition assessment and survival prediction in elderly cancer patients. Methods: This retrospective cohort analysis was conducted on a primary cohort of 1192 cancer patients aged 65 years or older enrolled from a multi-institutional registry, and a validation cohort of 300 elderly cancer patients treated at the First Affiliated Hospital of Sun Yat-sen University. Patients considered at-risk for malnutrition based on the NRS-2002 were assessed using the GLIM criteria. The association between the nutritional status and patients' overall survival (OS) was then analyzed by the Kaplan–Meier method and a Cox model. A nomogram was also established that included additional independent clinical prognostic variables. To determine the predictive accuracy and discriminatory capacity of the nomogram, the C-index, receiver operating characteristic (ROC) curve and calibration curve were evaluated. Results: The percentage of patients considered “at-risk” for malnutrition was 64.8% and 67.3% for the primary and validation cohorts, respectively. GLIM-defined malnutrition was diagnosed in 48.4% of patients in the primary cohort and 46.0% in the validation cohort. In the primary cohort, patients at risk of malnutrition (NRS-2002 ≥ 3) showed a worse OS than those with a NRS-2002 < 3 (HR 1.34, 1.10–1.64; p = 0.003). Additionally, patients with GLIM-defined severe malnutrition (HR1.71, 1.37–2.14; p < 0.001) or moderate malnutrition (HR1.35, 1.09–1.66; p = 0.006) showed a significantly shorter OS compared to those without malnutrition. The nomogram incorporating the domains of the GLIM with other variables was accurate, especially for predicting the 1- and 2-year overall survival rates. Conclusions: The GLIM criteria can be used in elderly cancer patients not only to assess malnutrition, but also to predict survival outcome. The nomogram developed based on the GLIM domains can provide a more accurate prediction of the prognosis than existing systems.

Background This study was sought to report the prevalence of malnutrition in elderly patients with cancer. Validate the predictive value of the nutritional assessment tool (Patient-Generated Subjective Global Assessment Short Form, PG-SGA SF) for clinical outcomes and assist the therapeutic decision. Methods This is a secondary analysis of a multicentric, observational cohort study. Elderly patients with cancer older than 65 years were enrolled after the first admission. Nutritional status was identified using the PG-SGA SF. Results Of the 2724 elderly patients included in the analysis, 65.27% of patients were male (n = 1778); the mean age was 71.00 ± 5.36 years. 31.5% of patients were considered malnourished according to PG-SGA SF. In multivariate analysis, malnutrition(PG-SGA SF > 5) was significantly associated with worse OS (HR: 1.47,95%CI:1.29–1.68), affects the quality of life, and was related to more frequent nutrition impact symptoms. During a median follow-up of 4.5 years, 1176 death occurred. The mortality risk was 41.10% for malnutrition during the first 12 months and led to a rate of 323.98 events per-1000-patient-years. All nutritional assessment tools were correlated with each other (PG-SGA SF vs. PG-SGA: r = 0.98; PG-SGA SF vs. GLIM[Global Leadership Initiative on Malnutrition]: r = 0.48, all P

Objectives: Since the launch of Global Leadership Initiative on Malnutrition (GLIM), there has been an urgent need to validate the new criteria, especially in patients with cancer. The aim of this study was to evaluate and validate the use of the GLIM criteria in patients with cancer. Method: This multicenter cohort study compared the GLIM with the scored Patient-Generated Subjective Global Assessment (sPG-SGA). The 1-y survival rate, multivariate Cox regression analysis, κ-value, sensitivity, specificity, receiver operating characteristic (ROC) curve, and time-dependent ROC analysis were applied to identify the performance of the GLIM. Results: Among the 3777 patients in the study, 50.9% versus 49.1% or 36.3% versus 63.7% of the patients were defined as well-nourished and malnourished by GLIM or sPG-SGA, respectively. GLIM presented moderate consistency (κ = 0.54, P < 0.001), fair sensitivity and specificity (70.5 and 88.3%) compared with sPG-SGA. There was no difference in the 1-y survival rate in malnourished patients (76.9 versus 76.4%, P = 0.711), but it was significantly different in well-nourished patients (85.8 versus 90.3%, P < 0.001) between GLIM and sPG-SGA. The above difference was eliminated after omitted nutritional risk screening (NRS)-2002 screening before GLIM (88.1 versus 90.3%, P = 0.078). Omitting NRS-2002 screening before GLIM did not change the 1-y survival rate in well-nourished or malnourished patients by GLIM with NRS-2002 screening (76.9 versus 78.9%, P = 0.099; 85.8% versus 88.1%, P = 0.092) although it significantly raised the rate of malnutrition to 72.5%. The combination of “weight loss and cancer” showed better performance than other combinations. Conclusions: GLIM could be a convenient alternative to sPG-SGA in nutrition assessment for patients with cancer. The combination of “weight loss and cancer” was better than other combinations. Considering the higher risk for malnutrition in patients with cancer, NRS-2002 screening may not be needed before GLIM.

Summary Background & aims The Global Leadership Initiative on Malnutrition (GLIM) released new universal criteria for diagnosing and grading malnutrition, and calls for further investigations not only in different clinical setting but also in GLIM itself including reference value, combination and weight of different GLIM criteria. This study aimed to weigh the GLIM criteria and develop a scored-GLIM system, and then validate as well as evaluate its application in nutritional assessment and survival prediction for patients with cancer. Design A total of 3547 patients in the primary cohort and 415 patients in the validation cohort were included in the study. Patients’ nutritional status were retrospectively assessed using the GLIM criteria. Kaplan–Meier survival curves and multivariate Cox regression analyses were performed to analyze the association between nutritional status and overall survival (OS). A nomogram was produced to quantify the GLIM criteria and develop the scored-GLIM system. C-index, receiver operating characteristic (ROC) curve and calibration curve analyses were performed to validate the predictive accuracy and discriminatory capacity of the scored-GLIM. Finally, a decision curve was applied to assess the clinical utility of the scored-GLIM system. Results In the primary cohort, 70.3% of patients were diagnosed as malnutrition. The malnutrition severity grading according to the GLIM criteria were associated with the prognosis of patients with cancer (HR 1.42, 1.23 to 1.65 for moderate malnutrition; HR 1.80,1.84 to 2.09 for severe malnutrition). The weight of each GLIM criteria was calculated, and unintentional weight loss was the most determining factor acting upon mortality (HR 1.82, 1.64 to 2.10 for stage II and HR 1.50, 1.31 to 1.73 for stage I). A nomogram was constructed by four factors of GLIM to weigh the GLIM criteria. The areas under the ROC curve were 65.3 (1-year ROC) and 65.5 (3-year ROC), and the C-index was 0.62, and the calibration curves fitted well. Decision curve analysis demonstrated the clinical usefulness of the scored-GLIM system. Conclusion The accuracy and net clinical benefit of scored-GLIM system were similar to scored-PG-SGA but higher than GLIM both in nutrition assessment and in survival prediction for patients with cancer. These findings, along with its time-savings advantages over scored-PG-SGA, suggest scored-GLIM be a better nutritional assessment tool.