A simplified prediction model for early intrahepatic recurrence after hepatectomy for patients with unilobar hepatocellular carcinoma without macroscopic vascular invasion: An implication for adjuvant therapy and postoperative surveillance

Abstract

Background: An accurate prediction model of early recurrence of hepatocellular carcinoma (HCC) after hepatectomy is important to ascertain the postoperative adjuvant treatment and surveillance.

Methods: This is a retrospective cohort study including 1125 patients with HCC underwent curative hepatic resection. They were randomly divided into training (n = 562) and validation (n = 563) sets. Early intrahepatic recurrence within 18 months from surgery is the primary outcome. In the training set, a prediction scoring model (Recurrent Liver Cancer Score RLCS) was developed, which was legitimised in the validation set.

Results: RLCS was developed based on four clinicopathologic risk factors (serum alpha fetoprotein, tumor size, multiple tumors or satellite nodules, and microvascular invasion). Low-risk and high-risk groups had statistically significant differences in early recurrence rates (18% vs. 43.8%). The 5-year recurrence-free survival rates of low risk and high risk groups were 52.9% and 27.8%, respectively. This model showed good calibration and discriminatory ability in the validation set (c-index of 0.647).

Conclusion: RLCS is a user-friendly prediction scoring model which can accurately predict the occurrence of early intrahepatic recurrence of HCC. It establishes the basis of postoperative adjuvant treatment and surveillance in future studies.