Exploring Body Composition Profiles in Patients with Gastrointestinal Cancers: A Cross-Sectional Analysis of the...

Body composition (BC) analysis may integrate assessment of nutritional risk in patients with gastrointestinal cancers. Applying unsupervised machine learning techniques, we derived BC profiles (BCPs) and investigated their association with malnutrition risk and quality of life. This cross-sectional analysis includes gastrointestinal cancer patients enrolled in the NUTRItional and sarcopenia SCREENing project, part of the ONCOCAMP study (ClinicalTrials.gov ID: NCT06270602). Malnutrition assessment was performed using the NRS-2002, anthropometry and BC analysis; HRQoL was evaluated with the EORTC QLQ-C30 questionnaire. Principal component analysis and k-means clustering identified BCPs. Data from 189 patients (mean age: 66.3 ± 11.2 years) with gastric (37%), pancreatic (26.5%), rectal (24.3%) and hepatocellular carcinoma (12.2%) were analyzed. Overall, 36.5% of patients were at nutritional risk (NRS-2002 ≥ 3). Two BC clusters, High Muscle Profile (HMP) and Low Muscle Profile (LMP), were derived. Although no statistically significant association was observed in the overall cohort, multivariable analysis stratified by gender identified an association between LMP and nutritional risk among male patients (OR = 3.77, 95% CI: 1.08-14.3, p = 0.042); however, this finding should be considered exploratory. Nutritional risk, but not BC profiles, was associated with poorer Summary Score (β = 8.0, 95% CI: -14 to -2.3, p = 0.007) and higher Symptom Score (β = 9.8, 95% CI:4.5 to 15, p < 0.001). These preliminary results warrant further confirmation in larger, adequately powered longitudinal cohorts. Future studies should determine whether BCPs provide additional value beyond established nutritional screening and individual BC parameters in clinical practice.