RESUMEN
BACKGROUND: The efficacy of conversion therapy for patients with unresectable hepatocellular carcinoma (HCC) is a common clinical concern. AIM: To analyse the prognostic factors of overall survival (OS) in patients with unresectable HCC who received conversion therapy. METHODS: One hundred and fifty patients who met the inclusion criteria were enrolled and divided into a training cohort (n = 120) and a validation cohort (n = 30). Using the independent risk factors in the training cohort, a nomogram model was constructed to predict OS for patients treated with transarterial chemoembolization following hepatic resection. The nomogram was internally validated with the bootstrapping method. The predictive performance of nomogram was assessed by Harrell's concordance index (C-index), calibration plot and time-dependent receiver operating characteristic curves and compared with six other conventional HCC staging systems. RESULTS: Multivariate Cox analysis identified that albumin, blood urea nitrogen, gamma-glutamyl transpeptidase to platelet ratio, platelet to lymphocyte ratio, macrovascular invasion and tumour number were the six independent prognostic factors correlated with OS in nomogram model. The C-index in the training cohort and validation cohort were 0.752 and 0.807 for predicting OS, which were higher than those of the six conventional HCC staging systems (0.563 to 0.715 for the training cohort and 0.458 to 0.571 for the validation cohort). The calibration plots showed good consistency between the nomogram prediction of OS and the actual observations of OS. Decision curve analyses indicated satisfactory clinical utility. With a total nomogram score of 196, patients were accurately classified into low-risk and high-risk groups. Furthermore, we have deployed the model into online calculators that can be accessed for free at https://ctmodelforunresectablehcc.shinyapps.io/DynNomapp/. CONCLUSION: The nomogram achieved optimal individualized prognostication of OS in HCC patients who received conversion therapy, which could be a useful clinical tool to help guide postoperative personalized interventions and prognosis judgement.