Development of pre and post-operative models to predict early recurrence of hepatocellular carcinoma after surgical resection.

BACKGROUND & AIMS: Resection is the most widely used potentially curative treatment for patients with early hepatocellular carcinoma (HCC). However, recurrence within 2 years occurs in 30-50% of patients, being the major cause of mortality. Herein, we describe 2 models, both based on widely available clinical data, which permit risk of early recurrence to be assessed before and after resection.

METHODS: A total of 3,903 patients undergoing surgical resection with curative intent were recruited from 6 different centres. We built 2 models for early recurrence, 1 using preoperative and 1 using pre and post-operative data, which were internally validated in the Hong Kong cohort. The models were then externally validated in European, Chinese and US cohorts. We developed 2 online calculators to permit easy clinical application.

RESULTS: Multivariable analysis identified male gender, large tumour size, multinodular tumour, high albumin-bilirubin (ALBI) grade and high serum alpha-fetoprotein as the key parameters related to early recurrence. Using these variables, a preoperative model (ERASL-pre) gave 3 risk strata for recurrence-free survival (RFS) in the entire cohort - low risk: 2-year RFS 64.8%, intermediate risk: 2-year RFS 42.5% and high risk: 2-year RFS 20.7%. Median survival in each stratum was similar between centres and the discrimination between the 3 strata was enhanced in the post-operative model (ERASL-post) which included 'microvascular invasion'.

CONCLUSIONS: Statistical models that can predict the risk of early HCC recurrence after resection have been developed, extensively validated and shown to be applicable in the international setting. Such models will be valuable in guiding surveillance follow-up and in the design of post-resection adjuvant therapy trials.

LAY SUMMARY: The most effective treatment of hepatocellular carcinoma is surgical removal of the tumour but there is often recurrence. In this large international study, we develop a statistical method that allows clinicians to estimate the risk of recurrence in an individual patient. This facility enhances communication with the patient about the likely success of the treatment and will help in designing clinical trials that aim to find drugs that decrease the risk of recurrence.