Validation of GLIM malnutrition criteria in cancer patients undergoing major abdominal surgery: A large-scale prospective study

Tan, Shanjun; Wang, Junjie; Zhou, Feng; Tang, Min; Zhang, Yanni; Yan, Mingyue; Li, Shuhao; Zhang, Zhige; Wu, Guohao

doi:10.1016/j.clnu.2022.01.010

Cited by 19 publications

(23 citation statements)

References 47 publications

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“…Applying our inclusion and exclusion criteria resulted in the further exclusion of eighteen publications. Finally, 15 cohort studies ( 16 – 30 ) were pooled into the current analysis ( Figure 1 ). Because Huang ( 18 ), Xu ( 28 ) and Song ( 29 ) reported different outcomes of interest or enrolled patients with different cancer types, they were all included in the present study even though they originated from a same cohort.…”

Section: Resultsmentioning

confidence: 99%

“…Details of the study characteristics and NOS scores were described in Table 1 . All enrolled papers were published between 2020 and 2022, including nine from China ( 18 , 20 , 21 , 24 , 26 – 30 ), and one each from Japan ( 19 ), Australia ( 22 ), Greece ( 16 ), Turkey ( 17 ), Spain ( 23 ) and South Korea ( 25 ). Four articles ( 16 , 20 , 23 , 30 ) were designed as prospective, while eleven ( 17 – 19 , 21 , 22 , 24 – 29 ) were retrospective.…”

Section: Resultsmentioning

confidence: 99%

“…All enrolled papers were published between 2020 and 2022, including nine from China ( 18 , 20 , 21 , 24 , 26 – 30 ), and one each from Japan ( 19 ), Australia ( 22 ), Greece ( 16 ), Turkey ( 17 ), Spain ( 23 ) and South Korea ( 25 ). Four articles ( 16 , 20 , 23 , 30 ) were designed as prospective, while eleven ( 17 – 19 , 21 , 22 , 24 – 29 ) were retrospective. Four articles ( 31 – 34 ) enrolled patients with all types of cancer, three ( 18 , 27 , 28 ) enrolled patients with gastric cancer, three ( 19 , 20 , 26 ) enrolled patients with esophageal cancer, one ( 16 ) enrolled patients with gastric/pancreatic/hepatic/colorectal cancer, one ( 30 ) enrolled patients with gastric/pancreatic/biliary/colorectal cancer.…”

Section: Resultsmentioning

confidence: 99%

“…Four articles ( 16 , 20 , 23 , 30 ) were designed as prospective, while eleven ( 17 – 19 , 21 , 22 , 24 – 29 ) were retrospective. Four articles ( 31 – 34 ) enrolled patients with all types of cancer, three ( 18 , 27 , 28 ) enrolled patients with gastric cancer, three ( 19 , 20 , 26 ) enrolled patients with esophageal cancer, one ( 16 ) enrolled patients with gastric/pancreatic/hepatic/colorectal cancer, one ( 30 ) enrolled patients with gastric/pancreatic/biliary/colorectal cancer. The remaining three articles included patients diagnosed with hematologic cancer ( 17 ), pancreatic cancer ( 25 ), or colorectal cancer ( 29 ), respectively.…”

Section: Resultsmentioning

confidence: 99%

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Malnutrition diagnosed by the Global Leadership Initiative on Malnutrition criteria predicting survival and clinical outcomes of patients with cancer: A systematic review and meta-analysis

et al. 2022

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ObjectivesRecently, some cohorts have looked into the use of Global Leadership Initiative on Malnutrition (GLIM) criteria in cancer patients. The objective of the current meta-analysis was to determine its utility in predicting clinical and survival outcomes for cancer patients.MethodSearching and screening literature from PubMed, Web of Science and Embase until September 13, 2022 was performed by two researchers independently. According to the exclusion and inclusion criteria, articles reporting the impact of malnutrition diagnosed by GLIM on long-term survival and clinical outcomes were included. Data of interest were also extracted from the included papers. The stability of the pooled results was evaluated using sensitivity analysis. With the aid of subgroup analysis, heterogeneity was revealed. To assess publication bias, Egger’s and Begg’s tests were conducted. The influence of publication bias on the pooling risk estimate was examined using a trim-and-fill analysis.Results15 studies that qualified for our study were identified. Pooled hazard ratio (HR) from both multivariate and univariate regression analysis showed a worse overall survival in GLIM-defined malnourished cancer patients than those in well-nourished status. Meanwhile, disease-free survival was also poorer in malnourished patients. Moreover, pooled odds ratio (OR) demonstrated that malnourished cancer patients were more likely to develop overall postoperative complications, complications ≥ Clavien-Dindo grade IIa and complications ≥ Clavien-Dindo grade IIIa. Two articles reported negative relation between GLIM-defined malnutrition and 30-day readmission/mortality.ConclusionGLIM-defined malnutrition possesses value in predicting poorer survival and clinical outcomes for cancer patients.Systematic review registration[https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=321094], identifier [CRD42022321094].

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Malnutrition diagnosed by the Global Leadership Initiative on Malnutrition criteria predicting survival and clinical outcomes of patients with cancer: A systematic review and meta-analysis

et al. 2022

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“…As long as at least one phenotypic criterion and one etiological criterion are met, malnutrition can be diagnosed. Since its publication, GLIM has been assessed by many researchers for its accuracy in predicting clinical outcomes in patients with cancer, cardiovascular diseases, surgery, and other diseases in comparison with other methods [ 13 , 14 , 15 , 16 ]. It has been found that the incidence of malnutrition diagnosed by GLIM is higher than SGA and ESPEN 2015 [ 17 , 18 ].…”

Section: Introductionmentioning

confidence: 99%

Machine Learning-Based Prediction of In-Hospital Complications in Elderly Patients Using GLIM-, SGA-, and ESPEN 2015-Diagnosed Malnutrition as a Factor

et al. 2022

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Background: Malnutrition is prevalent in elderly inpatients and is associated with various adverse outcomes during their hospital stay, but the diagnosis of malnutrition still lacks widely applicable criteria. This study aimed to investigate the association of malnutrition diagnosed with the SGA, ESPEN 2015, and GLIM criteria, respectively, with in-hospital complications in elderly patients. Method: Hospitalized patients over 65 years old who had been assessed with the SGA guideline for malnutrition at admission were retrospectively recruited from a large observational cohort study conducted in 34 level-A tertiary hospitals in 18 cities in China from June to September 2014. Malnutrition was then retrospectively diagnosed using the GLIM and ESPEN 2015 criteria, respectively, for comparison with the results of the SGA scale. The risk factors for malnutrition were analyzed using logistic regression, and the value of the three diagnostic criteria in predicting the in-hospital complications was subsequently explored using multivariate regression and the random forest machine learning algorithm. Results: A total of 2526 subjects who met the inclusion and exclusion criteria of the study were selected from the 7122 patients in the dataset, with an average age of 74.63 ± 7.12 years, 59.2% male, and 94.2% married. According to the GLIM, SGA, and ESPEN 2015 criteria, the detection rates of malnutrition were 37.8% (956 subjects), 32.8% (829 subjects), and 17.0% (429 subjects), respectively. The diagnostic consistency between the GLIM and the SGA criteria is better than that between the ESPEN 2015 and the SGA criteria (Kappa statistics, 0.890 vs. 0.590). Logistic regression showed that the risk of developing complications in the GLIM-defined malnutrition patients is 2.414 times higher than that of normal patients, higher than those of the ESPEN 2015 and SGA criteria (1.745 and 1.786 times, respectively). The random forest classifications show that the GLIM criteria have a higher ability to predict complications in these elderly patients than the SGA and ESPEN 2015 criteria with a mean decrease in accuracy of 12.929, 10.251, and 5.819, respectively, and a mean decrease in Gini of 2.055, 1.817, and 1.614, respectively. Conclusion: The prevalence of malnutrition diagnosed with the GLIM criteria is higher than that of the SGA and the ESPEN 2015 criteria. The GLIM criteria are better than the SGA and the ESPEN 2015 criteria for predicting in-hospital complications in elderly patients.

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Development and validation of a cancer cachexia risk score for digestive tract cancer patients before abdominal surgery

Tan

Wang

Zhang

et al. 2023

J cachexia sarcopenia muscle

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Background Cancer cachexia is prevalent in digestive tract cancer patients and has significant impacts on prognosis; it is vital to identify individuals who are at risk of cancer cachexia to allow for appropriate evaluation and treatment. This study evaluated whether digestive tract cancer patients with a risk of cancer cachexia and who had a risk of adverse survival could be identified before abdominal surgery. Methods This large-scale cohort study involved patients who underwent abdominal surgery between January 2015 and December 2020 to treat digestive tract cancer. Participants were allocated to the development cohort, the validation cohort, or the application cohort. Univariate and multivariate analyses of the development cohort were performed to detect distinct risk variables for cancer cachexia to create a cancer cachexia risk score. The performance of the risk score across all the three cohorts was assessed through calculating the area under the receiver operating characteristic curve (AUC), as well as calibration and decision curves. We tested how well the score predicted survival outcomes in the application cohort. Results A total of 16 264 patients (median 64 years of age; 65.9% male) were included, with 8743 in the development cohort, 5828 in the validation cohort, and 1693 in the application cohort. Seven variables were identified as independent predictive factors and were included in the cancer cachexia risk score: cancer site, cancer stage, time from symptom onset to hospitalization, appetite loss, body mass index, skeletal muscle index, and neutrophil-lymphocyte ratio. The risk score predicting cancer cachexia owns a good discrimination, with the mean AUC of 0.760 (P < 0.001) in the development cohort, 0.743 (P < 0.001) in the validation cohort, and 0.751 (P < 0.001) in the application cohort, respectively, and had an excellent calibration (all P > 0.05). The decision curve analysis revealed net benefits of the risk score across a range of risk thresholds in the three cohorts. In the application cohort, compared with the high-risk group, the low-risk group experienced significantly longer overall survival [hazard ratio (HR) 2.887, P < 0.001] as well as relapse-free survival (HR 1.482, P = 0.01). Conclusions The cancer cachexia risk score constructed and validated demonstrated good performance in identifying those digestive tract cancer patients before abdominal surgery at a higher risk of cancer cachexia and unfavourable survival. This risk score can help clinicians to enhance their capabilities to screen for cancer cachexia, assess patient prognosis, and strengthen early decision-making on targeted approaches to attune cancer cachexia for digestive tract cancer patients before abdominal surgery.

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Validation of GLIM malnutrition criteria in cancer patients undergoing major abdominal surgery: A large-scale prospective study

Cited by 19 publications

References 47 publications

Malnutrition diagnosed by the Global Leadership Initiative on Malnutrition criteria predicting survival and clinical outcomes of patients with cancer: A systematic review and meta-analysis

Malnutrition diagnosed by the Global Leadership Initiative on Malnutrition criteria predicting survival and clinical outcomes of patients with cancer: A systematic review and meta-analysis

Machine Learning-Based Prediction of In-Hospital Complications in Elderly Patients Using GLIM-, SGA-, and ESPEN 2015-Diagnosed Malnutrition as a Factor

Development and validation of a cancer cachexia risk score for digestive tract cancer patients before abdominal surgery

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