Xi Zhang1, Meng Tang2, Qi Zhang2, Kang-Ping Zhang2, Zeng-Qing Guo3, Hong-Xia Xu4, Kai-Tao Yuan5, Miao Yu5, Marco Braga6, Tommy Cederholm7, Wei Li8, Rocco Barazzoni9, Han-Ping Shi10. 1. Department of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China; Department of Oncology, Capital Medical University, Beijing, 100038, China; Beijing International Science and Technology Cooperation Base for Cancer Metabolism and Nutrition, Beijing, 100038, China; Department of Radiotherapy, Affiliated Hospital of Hebei University, Baoding, 071000, China. 2. Department of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China; Department of Oncology, Capital Medical University, Beijing, 100038, China; Beijing International Science and Technology Cooperation Base for Cancer Metabolism and Nutrition, Beijing, 100038, China. 3. Department of Medical Oncology, Fujian Cancer Hospital, Fujian Medical University, Fujian, 350014, China. 4. Department of Clinical Nutrition, Daping Hospital, Third Military Medical University (Army Medical University), Chongqing, 400042, China. 5. Department of Surgery, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510515, China. 6. Department of Surgery, San Raffaele Hospital, Via Olgettina, Milan, Italy. 7. Department of Public Health and Caring Sciences, Clinical Nutrition and Metabolism, Uppsala University, Uppsala, Sweden. 8. Cancer Center of the First Hospital of Jilin University, Changchun, 130021, China. Electronic address: jdyylw@163.com. 9. Department of Medical, Surgical and Health Sciences-University of Trieste, Italy. Electronic address: barazzon@units.it. 10. Department of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China; Department of Oncology, Capital Medical University, Beijing, 100038, China; Beijing International Science and Technology Cooperation Base for Cancer Metabolism and Nutrition, Beijing, 100038, China. Electronic address: shihp@ccmu.edu.cn.
Abstract
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 & AIMS: Elderly cancerpatients 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 cancerpatients. METHODS: This retrospective cohort analysis was conducted on a primary cohort of 1192 cancerpatients aged 65 years or older enrolled from a multi-institutional registry, and a validation cohort of 300 elderly cancerpatients 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 cancerpatients 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.
Authors: Aleksandra Kaluźniak-Szymanowska; Roma Krzymińska-Siemaszko; Katarzyna Wieczorowska-Tobis; Ewa Deskur-Śmielecka Journal: Int J Environ Res Public Health Date: 2022-01-18 Impact factor: 3.390