Evaluation of the Global Leadership Initiative on Malnutrition Criteria Using Different Muscle Mass Indices for Diagnosing Malnutrition and Predicting Survival in Lung Cancer Patients.
lung cancer
malnutrition
muscle mass
prediction
survival
Journal
JPEN. Journal of parenteral and enteral nutrition
ISSN: 1941-2444
Titre abrégé: JPEN J Parenter Enteral Nutr
Pays: United States
ID NLM: 7804134
Informations de publication
Date de publication:
03 2021
03 2021
Historique:
revised:
21
04
2020
received:
06
03
2020
accepted:
04
05
2020
pubmed:
10
5
2020
medline:
22
4
2021
entrez:
10
5
2020
Statut:
ppublish
Résumé
Malnutrition is prevalent in lung cancer (LC) patients, yet there are no globally accepted criteria for diagnosing malnutrition. Recently, the Global Leadership Initiative on Malnutrition (GLIM) criteria were proposed. However, the role of these criteria in prospective LC cohorts remains unclear. We performed a multicenter, observational cohort study including 1219 LC patients. Different anthropometric measures were compared for assessment of reduced muscle mass (RMM) in the GLIM criteria. Least absolute shrinkage and selection operator and multivariate Cox regressions were performed to analyze the association between the GLIM criteria and survival. Independent prognostic predictors were incorporated to develop a nomogram for individualized survival prediction, and decision curve was applied to assess the clinical significance of the nomogram. Patients in the stage II (severe) malnutrition group, diagnosed using combined calf circumference (CC) plus body weight-standardized handgrip strength (HGS/W) criteria, had the highest hazard ratio (HR, 2.07; 95%CI, 1.50-2.86) compared with other methods used to evaluate RMM. The GLIM criteria diagnosed malnutrition in 24% of cases (292 patients, using the CC and HGS/W criteria) and were effective for determining the nutrition status of LC patients. GLIM-diagnosed malnutrition was an independent risk factor for survival, and malnutrition severity was monotonically associated with death hazards (P = .002). The GLIM nomogram showed good performance in predicting the survival of LC patients, and the decision-curve analysis demonstrated that the nomogram was clinically useful. These findings support the effectiveness of GLIM in diagnosing malnutrition and predicting survival among LC patients.
Sections du résumé
BACKGROUND
Malnutrition is prevalent in lung cancer (LC) patients, yet there are no globally accepted criteria for diagnosing malnutrition. Recently, the Global Leadership Initiative on Malnutrition (GLIM) criteria were proposed. However, the role of these criteria in prospective LC cohorts remains unclear.
METHODS
We performed a multicenter, observational cohort study including 1219 LC patients. Different anthropometric measures were compared for assessment of reduced muscle mass (RMM) in the GLIM criteria. Least absolute shrinkage and selection operator and multivariate Cox regressions were performed to analyze the association between the GLIM criteria and survival. Independent prognostic predictors were incorporated to develop a nomogram for individualized survival prediction, and decision curve was applied to assess the clinical significance of the nomogram.
RESULTS
Patients in the stage II (severe) malnutrition group, diagnosed using combined calf circumference (CC) plus body weight-standardized handgrip strength (HGS/W) criteria, had the highest hazard ratio (HR, 2.07; 95%CI, 1.50-2.86) compared with other methods used to evaluate RMM. The GLIM criteria diagnosed malnutrition in 24% of cases (292 patients, using the CC and HGS/W criteria) and were effective for determining the nutrition status of LC patients. GLIM-diagnosed malnutrition was an independent risk factor for survival, and malnutrition severity was monotonically associated with death hazards (P = .002). The GLIM nomogram showed good performance in predicting the survival of LC patients, and the decision-curve analysis demonstrated that the nomogram was clinically useful.
CONCLUSION
These findings support the effectiveness of GLIM in diagnosing malnutrition and predicting survival among LC patients.
Types de publication
Journal Article
Multicenter Study
Observational Study
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
607-617Subventions
Organisme : CIHR
Pays : Canada
Informations de copyright
© 2020 American Society for Parenteral and Enteral Nutrition.
Références
Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394-424.
Chen W, Zheng R, Baade PD, et al. Cancer statistics in China, 2015. CA Cancer J Clin. 2016;66(2):115-132.
Bagcchi S. Lung cancer survival only increases by a small amount despite recent treatment advances. Lancet Respir med. 2017;5(3):169.
Yang J, Zhu J, Zhang YH, et al. Lung cancer in a rural area of china: rapid rise in incidence and poor improvement in survival. Asian Pac J Cancer Prev. 2015;16(16):7295-302.
Kraak VI, Harrigan PB, Lawrence M, Harrison PJ, Jackson MA, Swinburn B. Balancing the benefits and risks of publicâ private partnerships to address the global double burden of malnutrition. Public Health Nutr. 2012;15(3):503-517.
Cederholm T, Barazzoni R, Austin P, et al. ESPEN guidelines on definitions and terminology of clinical nutrition. Clin Nutr. 2017;36(1):49-64.
Arends J, Bachmann P, Baracos V, et al. ESPEN guidelines on nutrition in cancer patients. Clin Nutr. 2017;36(1):11-48.
Bacha S, Mejdoub El Fehri S, Habibech S, et al. Impact of malnutrition in advanced non-small cell lung cancer. La Tunisie Medicale. 2018;96:59-63.
Li R, Wu J, Ma M, et al. Comparison of PG-SGA, SGA and body-composition measurement in detecting malnutrition among newly diagnosed lung cancer patients in stage IIIB/IV and benign conditions. Med Oncol. 2011;28(3):689-696.
Gioulbasanis I, Baracos VE, Giannousi Z, et al. Baseline nutritional evaluation in metastatic lung cancer patients: Mini Nutritional Assessment versus weight loss history. Ann Oncol. 2011;22(4):835-841.
Mohan A, Poulose R, Kulshreshtha I, et al. High prevalence of malnutrition and deranged relationship between energy demands and food intake in advanced non-small cell lung cancer. Eur J Cancer Care. 2017;26(4):e12503.
Go SI, Park MJ, Song HN, et al. Sarcopenia and inflammation are independent predictors of survival in male patients newly diagnosed with small cell lung cancer. Support Care Cancer. 2016;24(5):2075-2084.
Shen Q, Liu W, Quan H, et al. Prealbumin and lymphocyte-based prognostic score, a new tool for predicting long-term survival after curative resection of stage II/III gastric cancer. Br J Nutr. 2018;120(12):1359-1369.
Harada H, Yamashita Y, Misumi K, et al. Multidisciplinary team-based approach for comprehensive preoperative pulmonary rehabilitation including intensive nutritional support for lung cancer patients. PloS One. 2013;8(3):e59566.
Ross PJ, Ashley S, Norton A, et al. Do patients with weight loss have a worse outcome when undergoing chemotherapy for lung cancers? Br J Cancer. 2004;90(10):1905-1911.
Polanski J, Jankowska-Polanska B, Uchmanowicz I, et al. Malnutrition and quality of life in patients with non-small-cell lung cancer. Adv Exp Med Biol. 2017;1021:15-26.
Yang J, Zhang Q, Wang X. Role of nutritional support for postoperative recovery of respiratory function in patients with primary lung cancer. Oncol Lett. 2018;16:5978-5982.
Cederholm T, Jensen GL, Correia M, et al. GLIM criteria for the diagnosis of malnutrition-a consensus report from the global clinical nutrition community. Clin nutr. 2019;38(1):1-9.
Sanchez-Rodriguez D, Annweiler C, Marco E, et al. European academy for medicine of ageing session participants' report on malnutrition assessment and diagnostic methods: an international survey. Clin Nutr ESPEN. 2020;35:75-80.
Allard JP, Keller H, Gramlich L, Jeejeebhoy KN, Laporte M, Duerksen DR. GLIM criteria has fair sensitivity and specificity for diagnosing malnutrition when using SGA as comparator. Clin Nutr. Published December 20, 2019. https://doi.org/10.1016/j.clnu.2019.12.004
Karavetian M, Salhab N, Rizk R, Poulia KA. Malnutrition-inflammation score vs phase angle in the era of glim criteria: a cross-sectional study among hemodialysis patients in UAE. Nutrients. 2019;11(11).
Skeie E, Tangvik RJ, Nymo LS, Harthug S, Lassen K, Viste A. Weight loss and BMI criteria in GLIM's definition of malnutrition is associated with postoperative complications following abdominal resections-results from a National Quality Registry. Clin Nutr. 2019;39(5):1593-1599.
Contreras-Bolivar V, Sanchez-Torralvo FJ, Ruiz-Vico M, et al. GLIM criteria using hand grip strength adequately predict six-month mortality in cancer inpatients. Nutrients. 2019;11(9).
Maeda K, Ishida Y, Nonogaki T, Mori N. Reference body mass index values and the prevalence of malnutrition according to the global leadership initiative on malnutrition criteria. Clin Nutr. 2020;39(1):180-184.
Chun SW, Kim W, Choi KH. Comparison between grip strength and grip strength divided by body weight in their relationship with metabolic syndrome and quality of life in the elderly. PloS One. 2019;14(9):e0222040.
Huang YQ, Liang CH, He L, et al. Development and validation of a radiomics nomogram for preoperative prediction of lymph node metastasis in colorectal cancer. J Clin Oncol. 2016;34(18):2157-2164.
Sicotte M, Ledoux M, Zunzunegui MV, Ag Aboubacrine S, Nguyen VK. Reliability of anthropometric measures in a longitudinal cohort of patients initiating ART in West Africa. BMC Med Res Methodol. 2010;10:102.
Ulijaszek SJ, Kerr DA. Anthropometric measurement error and the assessment of nutritional status. BR J Nutr. 1999;82(3):165-177.
Akin S, Mucuk S, Ozturk A, et al. Muscle function-dependent sarcopenia and cut-off values of possible predictors in community-dwelling Turkish elderly: calf circumference, midarm muscle circumference and walking speed. Eur J Clin Nutr. 2015;69(10):1087-1090.
Kim S, Kim M, Lee Y, Kim B, Yoon TY, Won CW. Calf circumference as a simple screening marker for diagnosing sarcopenia in older korean adults: the Korean Frailty and Aging Cohort Study (KFACS). J Korean Med Sci. 2018;33(20):e151.
da Silva JR, Jr., Wiegert EVM, Oliveira L, Calixto-Lima L. Different methods for diagnosis of sarcopenia and its association with nutritional status and survival in patients with advanced cancer in palliative care. Nutrition. 2019;60:48-52.
Solheim TS, Laird BJA, Balstad TR, et al. A randomized phase II feasibility trial of a multimodal intervention for the management of cachexia in lung and pancreatic cancer. J Cachexia, Sarcopenia Muscle. 2017;8(5):778-788.
Kiss NK, Krishnasamy M, Isenring EA. The effect of nutrition intervention in lung cancer patients undergoing chemotherapy and/or radiotherapy: a systematic review. Nutr Cancer. 2014;66(1):47-56.
Evans WK, Nixon DW, Daly JM, et al. A randomized study of oral nutritional support versus ad lib nutritional intake during chemotherapy for advanced colorectal and non-small-cell lung cancer. J Clin Oncol. 1987;5(1):113-124.
Mar J, Arrospide A, Iruretagoiena ML, et al. Changes in lung cancer survival by TNM stage in the Basque country from 2003 to 2014 according to period of diagnosis. Cancer Epidemiol. 2020;65:101668.
Chang WP, Smith R, Lin CC. Age and rest-activity rhythm as predictors of survival in patients with newly diagnosed lung cancer. Chronobiol Int. 2018;35(2):188-197.
Itaya T, Yamaoto N, Ando M, et al. Influence of histological type, smoking history and chemotherapy on survival after first-line therapy in patients with advanced non-small cell lung cancer. Cancer Sci. 2007;98(2):226-230.
Grosu HB, Manzanera A, Shivakumar S, Sun S, Noguras Gonzalez G, Ost DE. Survival disparities following surgery among patients with different histological types of non-small cell lung cancer. Lung Cancer. 2020;140:55-58.
Japuntich SJ, Kumar P, Pendergast JF, et al. Smoking status and survival among a national cohort of lung and colorectal cancer patients. Nicotine Tob Res. 2019;21(4):497-504.
Friedel G, Fritz P, Goletz S, et al. Postoperative survival of lung cancer patients: are there predictors beyond TNM? Anticancer Res. 2013;33:1609-1619.
Okada S, Shimada J, Kato D, Tsunezuka H, Teramukai S, Inoue M. Clinical significance of prognostic nutritional index after surgical treatment in lung cancer. Ann Thorac Surg. 2017;104(1):296-30c2.
Zhou T, Hong S, Hu Z, et al. A systemic inflammation-based prognostic scores (mGPS) predicts overall survival of patients with small-cell lung cancer. Tumour Biol. 2015;36(1):337-343.
Wang Y, Qu X, Kam NW, et al. An inflammation-related nomogram for predicting the survival of patients with non-small cell lung cancer after pulmonary lobectomy. BMC Cancer. 2018;18(1):692.
Shahraki HR, Salehi A, Zare N. Survival prognostic factors of male breast cancer in Southern Iran: a LASSO-Cox regression approach. Asian Pac J Cancer Prev. 2015;16(15):6773-6777.