Body Composition Changes in Hepatocellular Carcinoma: Prediction of Survival to Transcatheter Arterial Chemoembolization in Combination With Clinical Prognostic Factors.

Treatment-related toxicities and decreased levels of patient performance during cancer therapy might contribute to body composition changes (BCC) and thereby impact outcomes. This study investigated the association between BCC during transcatheter arterial chemoembolization (TACE) and outcome in patients with hepatocellular carcinoma (HCC), and developed a nomogram for predicting survival in combination with clinical prognostic factors (CPF). Pretreatment and posttreatment computed tomography (CT) images of 75 patients with HCC who were treated between 2015 and 2018 were analyzed. The bone mineral density (BMD), cross-sectional area of paraspinal muscles (CSA), subcutaneous fat area (SFA), and visceral fat area (VFA) were measured from two sets of CT images. Count the changes in body composition during treatment and sort out the CPF of patients. Using cox regression models, CSA change, SFA change, VFA change, child-push class, and portal vein thrombosis were independent prognostic factors for overall survival (OS) (HR=5.932, 2.384, 3.140, 1.744, 1.794, respectively. < 0.05). Receiver operating characteristic curves (ROCs) showed the prediction model combination of BCC and CPF exhibited the highest predictive performance (AUC=0.937). Independent prognostic factors were all contained into the prognostic nomogram, the concordance index (C-index) of prognostic nomogram was 0.787 (95% CI, 0.675-0.887). Decision curve analysis (DCA) demonstrated that the prognostic nomogram was clinically useful. Nomogram-based risk classification systems were also constructed to facilitate risk stratification in HCC for optimization of clinical management. In conclusion, we identified CSA change, SFA change, VFA change, Child-Pugh class, and portal vein thrombosis were independent prognostic factors for HCC. The prognostic nomogram with a combination of BCC and CPF that can be applied in the individualized prediction of survival in patients with HCC after TACE.