Model containing sarcopenia and visceral adiposity can better predict the survival of hepatocellular carcinoma: A multicenter study

Abstract Aim: This study aimed to explore whether the addition of sarcopenia and visceral adiposity could improve the accuracy of model predicting progression-free survival (PFS) in hepatocellular carcinoma (HCC). Methods: In total, 394 patients with HCC from five hospitals were divided into the training and external validation datasets. Patients were initially treated by liver resection or transarterial chemoembolization. We evaluated adipose and skeletal muscle using preoperative computed tomography imaging and then constructed three predictive models, including metabolic (ModelMA), clinical–imaging (ModelCI), and combined (ModelMA-CI) models. Their discrimination, calibration, and decision curves were compared, to identify the best model. Nomogram and subgroup analysis was performed for the best model. Results: ModelMA-CI containing sarcopenia and visceral adiposity had good discrimination and calibrations(area under the curve for three-year PFS was 0.792in the training data set and 0.817 in the validation data set;similar results were achieved in one- and two-year PFS). ModelMA-CI had better accuracy than ModelCI and ModelMA. The performance of ModelMA-CI was not affected by treatments or disease stages. The high-risk subgroup(scored≥120) had a significantly shorter PFS (p<0.001) and poorer OS (p<0.001). Conclusions: The addition of sarcopenia and visceral adiposity improved accuracy in predicting PFS in HCC, which may provide additional insights in prognosis for HCC in subsequent studies.