The diagnostic accuracy of global leadership initiative on malnutrition in patients with cancer malnutrition: a meta-analysis_Chinese Journal of Evidence-Based Medicine

Authors：

WANG Xiaolin ¹ , ZHANG Jinhui ² , SHEN Xueli ¹ , LI Qiuyue ¹ , ZHOU Yanjun ³ ,  LIANG Tao ¹

1. School of Nursing, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100144, P. R. China;
2. Department of Medical Oncology, Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100021, P. R. China;
3. Department of Nursing, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing 100045, P. R. China;

Corresponding author：

LIANG Tao, Email: liangtao1@hotmail.com

Keywords：

GLIM; Cancer; Malnutrition; Diagnostic test; Meta-analysis

DOI：

10.7507/1672-2531.202404135

Video：

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Objective To systematically review the accuracy of the global leadership initiative on malnutrition (GLIM) in screening patients with cancer malnutrition. Methods The PubMed, Web of Science, Cochrane Library, Embase, CNKI, WanFang, SinoMed, and VIP databases were electronically searched to collect diagnostic tests related to the objects from January 2019 to March 2024. Two researchers independently screened the literature, extracted data, and assessed the risk of bias of the included studies. Meta-analysis was then performed using Stata 15.0 software. Results A total of 12 studies were included. The results of the meta-analysis showed that GLIM criteria for the diagnosis of malnutrition had a sensitivity of 0.69 (95%CI 0.63 to 0.76), specificity of 0.90 (95%CI 0.83 to 0.95), positive likelihood ratio of 7.18 (95%CI 4.17 to 12.35), negative likelihood ratio of 0.34 (95%CI 0.28 to 0.41), diagnostic odds ratio of 21.21 (95%CI 11.96 to 37.62), and area under the curve of 0.84 (95%CI 0.80 to 0.87). Conclusion Current evidence suggests that the GLIM criteria have diagnostic value as a tool for malnutrition in cancer patients, with moderate overall diagnostic efficacy.

1.	Wang Y, Liu Z, Zhang H, et al. Evaluation of different screening tools as the first step of the GLIM framework: a cross-sectional study of Chinese cancer patients in an outpatient setting. Nutr Clin Pract, 2024, 39(3): 702-713.
2.	Wiegert EVM, Padilha PC, Peres WAF. Performance of patient-generated subjective global assessment (PG-SGA) in patients with advanced cancer in palliative care. Nutr Clin Pract, 2017, 32(5): 675-681.
3.	Matsui R, Rifu K, Watanabe J, et al. Impact of malnutrition as defined by the GLIM criteria on treatment outcomes in patients with cancer: a systematic review and meta-analysis. Clin Nutr, 2023, 42(5): 615-624.
4.	Brown D, Loeliger J, Stewart J, et al. Relationship between global leadership initiative on malnutrition (GLIM) defined malnutrition and survival, length of stay and post-operative complications in people with cancer: a systematic review. Clin Nutr, 2023, 42(3): 255-268.
5.	Bauer J, Capra S, Ferguson M. Use of the scored patient-generated subjective global assessment (PG-SGA) as a nutrition assessment tool in patients with cancer. Eur J Clin Nutr, 2002, 56(8): 779-785.
6.	Arends J, Bachmann P, Baracos V, et al. ESPEN guidelines on nutrition in cancer patients. Clin Nutr, 2017, 36(1): 11-48.
7.	August DA, Huhmann MB. A. S. P. E. N. clinical guidelines: nutrition support therapy during adult anticancer treatment and in hematopoietic cell transplantation. JPEN J Parenter Enteral Nutr, 2009, 33(5): 472-500.
8.	Cederholm T, Jensen GL, Correia MITD, 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.
9.	Henriksen C, Paur I, Pedersen A, et al. Agreement between GLIM and PG-SGA for diagnosis of malnutrition depends on the screening tool used in GLIM. Clin Nutr, 2022, 41(2): 329-336.
10.	Zhang KP, Tang M, Fu ZM, et al. Global leadership initiative on malnutrition criteria as a nutrition assessment tool for patients with cancer. Nutrition, 2021, 91-92: 111379.
11.	Whiting PF, Rutjes AW, Westwood ME, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med, 2011, 155(8): 529-536.
12.	王巍巍, 杨智荣, 田金徽, 等. 诊断试验准确性研究系统评价和Meta分析摘要的报告规范(PRISMA-DTAforabstracts)解读. 中国循证医学杂志, 2021, 21(10): 1235-1240.
13.	张天嵩, 钟文昭. Meta-DiSc软件在诊断试验Meta分析中的应用. 循证医学, 2008, 8(2): 97-100,108.
14.	张俊, 徐志伟, 李克. 诊断性试验Meta分析的效应指标评价. 中国循证医学杂志, 2013, 13(7): 890-895.
15.	De Groot LM, Lee G, Ackerie A, et al. Malnutrition screening and assessment in the cancer care ambulatory setting: mortality predictability and validity of the patient-generated subjective global assessment short form (PG-SGA SF) and the GLIM criteria. Nutrients, 2020, 12(8): 2287.
16.	Zhang Z, Wan Z, Zhu Y, et al. Prevalence of malnutrition comparing NRS2002, MUST, and PG-SGA with the GLIM criteria in adults with cancer: a multi-center study. Nutrition, 2021, 83: 111072.
17.	Xu LB, Shi MM, Huang ZX, et al. Impact of malnutrition diagnosed using global leadership initiative on malnutrition criteria on clinical outcomes of patients with gastric cancer. JPEN J Parenter Enteral Nutr, 2022, 46(2): 385-394.
18.	李文成, 张帆, 牛励, 等. GLIM在胃癌病人营养不良诊断和预后评估中的价值研究及生存预测列线图模型的构建. 肠外与肠内营养, 2021, 28(6): 324-331.
19.	Liu Y, Kang J, Qi Z, et al. Comparison of GLIM and PG-SGA for predicting clinical outcomes of patients with esophageal squamous carcinoma resection. Nutr Hosp, 2023, 40(3): 574-582.
20.	Solon LA, Gomes KP, Da Luz MCL, et al. Comparison between GLIM and PG-SGA methods in the nutritional assessment of hospitalized oncological patients. Revista de Nutriç ã o, 2023, 36: 1.
21.	da Silva Couto A, Gonzalez MC, Martucci RB, et al. Predictive validity of GLIM malnutrition diagnosis in patients with colorectal cancer. JPEN J Parenter Enteral Nutr, 2023, 47(3): 420-428.
22.	Balcı C, Tufan G, Özdemir N, et al. GLIM criteria as a valid tool for nutrition assessment and mortality prediction in treatment-naïve patients with cancer. Nutr Clin Pract, 2023, 38(4): 798-806.
23.	芮红霞, 张冬婷, 张晓雨, 等. GLIM标准在胃肠道恶性肿瘤患者营养不良诊断中的应用研究. 肿瘤代谢与营养电子杂志, 2023, 10(1): 113-119.
24.	Pichardo MS, Esserman D, Ferrucci LM, et al. Adherence to the American cancer society guidelines on nutrition and physical activity for cancer prevention and obesity-related cancer risk and mortality in black and Latina women's health initiative participants. Cancer, 2022, 128(20): 3630-3640.
25.	Park SH, Knobf MT, Kerstetter J, et al. Adherence to American cancer society guidelines on nutrition and physical activity in female cancer survivors: results from a randomized controlled trial (Yale fitness intervention trial). Cancer Nurs, 2019, 42(3): 242-250.
26.	Ní Bhuachalla ÉB, Daly LE, Power DG, et al. Computed tomography diagnosed cachexia and sarcopenia in 725 oncology patients: is nutritional screening capturing hidden malnutrition. J Cachexia Sarcopenia Muscle, 2018, 9(2): 295-305.
27.	Martin L, Gioulbasanis I, Senesse P, et al. Cancer-associated malnutrition and CT-defined Sarcopenia and myosteatosis are endemic in overweight and obese patients. JPEN J Parenter Enteral Nutr, 2020, 44(2): 227-238.

1. Wang Y, Liu Z, Zhang H, et al. Evaluation of different screening tools as the first step of the GLIM framework: a cross-sectional study of Chinese cancer patients in an outpatient setting. Nutr Clin Pract, 2024, 39(3): 702-713.
2. Wiegert EVM, Padilha PC, Peres WAF. Performance of patient-generated subjective global assessment (PG-SGA) in patients with advanced cancer in palliative care. Nutr Clin Pract, 2017, 32(5): 675-681.
3. Matsui R, Rifu K, Watanabe J, et al. Impact of malnutrition as defined by the GLIM criteria on treatment outcomes in patients with cancer: a systematic review and meta-analysis. Clin Nutr, 2023, 42(5): 615-624.
4. Brown D, Loeliger J, Stewart J, et al. Relationship between global leadership initiative on malnutrition (GLIM) defined malnutrition and survival, length of stay and post-operative complications in people with cancer: a systematic review. Clin Nutr, 2023, 42(3): 255-268.
5. Bauer J, Capra S, Ferguson M. Use of the scored patient-generated subjective global assessment (PG-SGA) as a nutrition assessment tool in patients with cancer. Eur J Clin Nutr, 2002, 56(8): 779-785.
6. Arends J, Bachmann P, Baracos V, et al. ESPEN guidelines on nutrition in cancer patients. Clin Nutr, 2017, 36(1): 11-48.
7. August DA, Huhmann MB. A. S. P. E. N. clinical guidelines: nutrition support therapy during adult anticancer treatment and in hematopoietic cell transplantation. JPEN J Parenter Enteral Nutr, 2009, 33(5): 472-500.
8. Cederholm T, Jensen GL, Correia MITD, 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.
9. Henriksen C, Paur I, Pedersen A, et al. Agreement between GLIM and PG-SGA for diagnosis of malnutrition depends on the screening tool used in GLIM. Clin Nutr, 2022, 41(2): 329-336.
10. Zhang KP, Tang M, Fu ZM, et al. Global leadership initiative on malnutrition criteria as a nutrition assessment tool for patients with cancer. Nutrition, 2021, 91-92: 111379.
11. Whiting PF, Rutjes AW, Westwood ME, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med, 2011, 155(8): 529-536.
12. 王巍巍, 杨智荣, 田金徽, 等. 诊断试验准确性研究系统评价和Meta分析摘要的报告规范(PRISMA-DTAforabstracts)解读. 中国循证医学杂志, 2021, 21(10): 1235-1240.
13. 张天嵩, 钟文昭. Meta-DiSc软件在诊断试验Meta分析中的应用. 循证医学, 2008, 8(2): 97-100,108.
14. 张俊, 徐志伟, 李克. 诊断性试验Meta分析的效应指标评价. 中国循证医学杂志, 2013, 13(7): 890-895.
15. De Groot LM, Lee G, Ackerie A, et al. Malnutrition screening and assessment in the cancer care ambulatory setting: mortality predictability and validity of the patient-generated subjective global assessment short form (PG-SGA SF) and the GLIM criteria. Nutrients, 2020, 12(8): 2287.
16. Zhang Z, Wan Z, Zhu Y, et al. Prevalence of malnutrition comparing NRS2002, MUST, and PG-SGA with the GLIM criteria in adults with cancer: a multi-center study. Nutrition, 2021, 83: 111072.
17. Xu LB, Shi MM, Huang ZX, et al. Impact of malnutrition diagnosed using global leadership initiative on malnutrition criteria on clinical outcomes of patients with gastric cancer. JPEN J Parenter Enteral Nutr, 2022, 46(2): 385-394.
18. 李文成, 张帆, 牛励, 等. GLIM在胃癌病人营养不良诊断和预后评估中的价值研究及生存预测列线图模型的构建. 肠外与肠内营养, 2021, 28(6): 324-331.
19. Liu Y, Kang J, Qi Z, et al. Comparison of GLIM and PG-SGA for predicting clinical outcomes of patients with esophageal squamous carcinoma resection. Nutr Hosp, 2023, 40(3): 574-582.
20. Solon LA, Gomes KP, Da Luz MCL, et al. Comparison between GLIM and PG-SGA methods in the nutritional assessment of hospitalized oncological patients. Revista de Nutriç ã o, 2023, 36: 1.
21. da Silva Couto A, Gonzalez MC, Martucci RB, et al. Predictive validity of GLIM malnutrition diagnosis in patients with colorectal cancer. JPEN J Parenter Enteral Nutr, 2023, 47(3): 420-428.
22. Balcı C, Tufan G, Özdemir N, et al. GLIM criteria as a valid tool for nutrition assessment and mortality prediction in treatment-naïve patients with cancer. Nutr Clin Pract, 2023, 38(4): 798-806.
23. 芮红霞, 张冬婷, 张晓雨, 等. GLIM标准在胃肠道恶性肿瘤患者营养不良诊断中的应用研究. 肿瘤代谢与营养电子杂志, 2023, 10(1): 113-119.
24. Pichardo MS, Esserman D, Ferrucci LM, et al. Adherence to the American cancer society guidelines on nutrition and physical activity for cancer prevention and obesity-related cancer risk and mortality in black and Latina women's health initiative participants. Cancer, 2022, 128(20): 3630-3640.
25. Park SH, Knobf MT, Kerstetter J, et al. Adherence to American cancer society guidelines on nutrition and physical activity in female cancer survivors: results from a randomized controlled trial (Yale fitness intervention trial). Cancer Nurs, 2019, 42(3): 242-250.
26. Ní Bhuachalla ÉB, Daly LE, Power DG, et al. Computed tomography diagnosed cachexia and sarcopenia in 725 oncology patients: is nutritional screening capturing hidden malnutrition. J Cachexia Sarcopenia Muscle, 2018, 9(2): 295-305.
27. Martin L, Gioulbasanis I, Senesse P, et al. Cancer-associated malnutrition and CT-defined Sarcopenia and myosteatosis are endemic in overweight and obese patients. JPEN J Parenter Enteral Nutr, 2020, 44(2): 227-238.

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