CT assessment of body composition and liver fat fraction predicts prognosis in gastric cancer.

BACKGROUND

Prognosis in gastric cancer (GC) is closely linked to patients' nutritional and metabolic status. Although CT can evaluate body composition at different sites, few studies have combined these indicators for prognostic prediction.

METHODS

We retrospectively analyzed GC patients who underwent radical gastrectomy at two medical centers. Patients were randomly divided into a training cohort and a validation cohort at a 7:3 ratio. Preoperative CT images were used to quantify body composition and liver fat content. Cox regression identified prognostic indicators, and a combined score was constructed. A prognostic model integrating the combined score and clinicopathological factors was then constructed and compared with the pTNM staging system.

RESULTS

A total of 696 patients were included. Skeletal muscle density (SMD) and CT-derived liver fat fraction (LFF) were identified as independent prognostic factors. A combined score (SMD-LFF) was developed, stratifying patients into low-, intermediate-, and high-risk groups, with 5-year overall survival rates of 86.6%, 67.6%, and 42.3%, respectively (P < 0.001). Consistent stratification was observed in the validation cohort. Multivariable analysis identified SMD-LFF, postoperative chemotherapy, lymphovascular invasion, pT stage, and pN stage as independent predictors, which were incorporated into a nomogram. The nomogram showed superior predictive performance and clinical net benefit compared with the pTNM staging system.

CONCLUSION

The SMD-LFF score, combining skeletal muscle density and liver fat content, is an independent prognostic factor for GC patients. The nomogram integrating this score with clinicopathological variables outperforms the pTNM staging system in predicting postoperative survival and recurrence risk.