Adipose Tissue Quantification Improves the Prognostic Value of GLIM Criteria in Advanced Gastric Cancer Patients.
Geum Jong SongHyein AhnMyoung Won SonJong Hyuk YunMoon-Soo LeeSang Mi LeePublished in: Nutrients (2024)
The present study investigated whether the risk of recurrence after curative surgery could be further stratified by combining the Global Leadership Initiative on Malnutrition (GLIM) criteria and changes in subcutaneous (SAT) and visceral (VAT) adipose tissue mass after surgery in patients with advanced gastric cancer (AGC). This study retrospectively analyzed 302 patients with AGC who underwent curative surgery. Based on the GLIM criteria, patients were classified into malnourished and non-malnourished groups. The cross-sectional areas of SAT and VAT were measured from preoperative and 6-month post-operative computed tomography (CT) images. Multivariate survival analyses demonstrated that GLIM-defined malnutrition ( p = 0.008) and loss of VAT after surgery ( p = 0.008) were independent risk factors for recurrence-free survival (RFS). Evaluation of the prognostic value of combining the two independent predictors showed that malnourished patients with a marked loss of VAT had the worst 5-year RFS rate of 35.2% ( p < 0.001). Preoperative GLIM-defined malnutrition and a loss of VAT during the first 6 months after surgery were independent predictors for RFS in patients with AGC. Changes in the VAT area after surgery could further enhance the prognostic value of the GLIM criteria for predicting the risk of gastric cancer recurrence.
Keyphrases
- free survival
- adipose tissue
- computed tomography
- minimally invasive
- cross sectional
- insulin resistance
- prognostic factors
- end stage renal disease
- coronary artery bypass
- patients undergoing
- magnetic resonance imaging
- high fat diet
- ejection fraction
- newly diagnosed
- coronary artery disease
- deep learning
- squamous cell carcinoma
- type diabetes
- quality improvement
- rectal cancer
- peritoneal dialysis
- image quality
- neoadjuvant chemotherapy
- metabolic syndrome
- magnetic resonance
- percutaneous coronary intervention
- radiation therapy
- patient reported outcomes
- machine learning
- acute coronary syndrome
- mass spectrometry
- surgical site infection
- convolutional neural network
- high resolution
- locally advanced