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Incorporating CT-Derived Body Composition Analysis Into the Global Leadership Initiative on Malnutrition Criteria Is Associated With Overall Survival: Findings From an International Cancer Cohort

  • Clodagh Scannell
  • , Erin Stella Sullivan
  • , Ross D. Dolan
  • , Josh McGovern
  • , Marie Fallon
  • , Barry J. Laird
  • , Derek G. Power
  • , Aoife M. Ryan
  • University College Cork
  • King's College London
  • University of Glasgow
  • University of Edinburgh
  • Mercy & Cork University Hospitals

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Cancer-associated malnutrition is highly prevalent and linked to adverse outcomes. However, studies evaluating malnutrition using the Global Leadership Initiative on Malnutrition (GLIM) criteria with inclusion of computed tomography (CT)-derived muscle mass are limited, particularly in Caucasian oncology populations. Moreover, the prevalence of GLIM-defined malnutrition and its association with overall survival across different treatment intents remains insufficiently characterized. Objective: This study investigates whether incorporating CT-derived body composition assessment into the GLIM criteria improves the detection of malnutrition in oncology patients and evaluates its association with overall survival across different treatment intent groups. Design: Secondary analysis of data from 2 observational, prospective studies in Ireland and the United Kingdom that both examined the effect of nutritional and inflammatory status on survival in patients. GLIM phenotypic and etiologic criteria were retrospectively applied using data available from these studies. Reduced muscle mass was derived from CT. Participants/Setting: Data were available for 1405 patients enrolled between 2011 and 2016; 1118 had evaluable CT scans. Treatment intent included curative (n = 428), palliative active treatment (n = 873), and supportive care (n = 104). Main Outcome: Prevalence of GLIM-diagnosed malnutrition incorporating CT muscle assessment and its association with overall survival (months) by treatment intent. Survival analysis was carried out using Kaplan-Meier curves and Cox regression. Statistical Analysis: Descriptive statistics characterized clinical characteristics and nutritional status. Analyses were conducted in SPSS, and statistical significance was considered at P < .05. Results: GLIM-malnutrition was identified in 40.4% (22.6% moderate; 17.8% severe). Among those with CT scans, 42.2% had low muscle mass, and only 24.8% had experienced >5% weight loss. CT analysis identified GLIM malnutrition in 22.8% of patients missed by weight/body mass index (BMI) criteria. Median follow-up was 102.4 months. Median survival was 30.4 months for well-nourished patients vs 13.5 months (moderate) and 6.4 months (severe) for malnourished patients (P < .001). Adjusted hazard ratios for death were 1.379 (moderate malnutrition) and 1.799 (severe malnutrition) (P < .001). Conclusion: GLIM-diagnosed malnutrition, particularly when incorporating CT-derived muscle mass, is common and strongly predicts poor survival across treatment intents. CT-based assessment identifies patients with muscle wasting who may be missed by conventional criteria, supporting its integration into GLIM phenotyping.

Original languageEnglish
Article number156367
JournalJournal of the Academy of Nutrition and Dietetics
Volume126
Issue number8
DOIs
Publication statusPublished - Aug 2026
Externally publishedYes

Keywords

  • Cancer
  • Diagnostic criteria
  • Malnutrition
  • Nutrition assessment
  • Survival

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