Frontiers in Nutrition · 2022 · 29 citations · 30 references
MedicineOncologySurgeryGastrointestinal OncologySurgical OncologySurvival AnalysisCancer Survival AnalysisMuscle Mass AssessmentComputed Tomography Muscle AnalysisDisease-free Survival AnalysisDisease-free Survival AssessmentMuscle Mass MaintenanceOverall MortalitySkeletal ChangesSkeletal Muscle AtrophySkeletal Muscle Index
Background Skeletal muscle mass deterioration is common in gastric cancer (GC) patients and is linked to poor prognosis. However, information regarding the effect of skeletal muscle mass changes in the postoperative period is scarce. This study was to investigate the link between postoperative loss of skeletal muscle mass and survival following GC surgery. Methods Patients who underwent GC surgery between January 2015 and December 2016 were recruited into the study. Computed tomography at L3 vertebral level was used to examine skeletal muscle index prior to surgery and about 6 months after surgery. Skeletal muscle index changes were categorized as presence or absence of ≥5% loss. Overall survival (OS) and disease-free survival (DFS) were analyzed, and Cox proportional hazard models used to identify their predictors. Results The study comprised of 318 gastric cancer patients of which 63.5% were male. The group's mean age was 58.14 ± 10.77 years. Sixty-five patients experienced postoperative skeletal muscle index loss ≥5% and had poorer OS ( P = 0.004) and DFS ( P = 0.020). We find that postoperative skeletal muscle index loss ≥ 5% predicts OS [hazard ratio (HR): 2.769, 95% confidence interval (CI): 1.865–4.111; P < 0.001] and DFS (HR: 2.533, 95% CI: 1.753–3.659; P < 0.001). Conclusions Loss of skeletal muscle mass postoperatively is linked to poor survival following GC surgery. Further studies are needed to determine whether stabilizing or enhancing skeletal muscle mass after surgery improves survival.
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Sarcopenia: revised European consensus on definition and diagnosis
Alfonso J. Cruz‐Jentoft, Gülistan Bahat, Jürgen M. Bauer et al. · Age and Ageing · 2018 · 14K citations · Full text