A novel nomogram for prediction of intrahepatic recurrence-free survival in patients with HCC followed by radiofrequency ablation.

Objective: Although radiofrequency ablation (RFA) has been considered as the favourable treatment option for hepatocellular carcinoma (HCC), there still exist some challenges for new recurrence after RFA. The present study aims to determine the factors affecting recurrence and develop an effective model to predict intrahepatic recurrence-free survival (RFS).

Methods: Patients with HCC followed by RFA between 2000 and 2021 were included in this study. Multivariable Cox regression analysis was used to determine the independent prognostic factors and establish the nomogram predicting intrahepatic RFS after RFA. The predictive performance of the nomogram was assessed according to the C-index, calibration plots, and Kaplan-Meier curves stratified by the tertiles.

Results: A total of 801 sessions in 660 patients (including 1155 lesions) were enrolled into this study. Intrahepatic new recurrence was observed in all patients during the follow-up, and the mean intrahepatic RFS was 21.9 months in the present cohort. According to multivariate COX regression analysis, five independent prognostic factors affecting intrahepatic RFS were determined, including age, Child-Pugh class, tumour distribution, number of tumours, and a-fetoprotein (AFP). Based on all independent prognostic factors, the nomogram model was developed and evaluated, which achieved favourable discrimination and calibration.

Conclusion: This study established five independent prognostic factors and constructed a nomogram model to predict intrahepatic RFS for HCC patients followed by RFA. It could better help clinicians select RFA candidates, as well as offering the important information about whether patients need receive comprehensive treatment to prevent new recurrence after RFA.

Advances in knowledge: (1) In this study, 5 preoperative clinic-pathological variables were determined as the independent prognostic factors affecting RFS after RFA in the current largest sample size. (2) Based on these independent prognostic factors, a prognostic nomogram predicting RFS after RFA was established, which may be used to select patients who benefit from RFA and could help both surgeons and patients provide useful information for choosing the personalized treatment.