A Model for Adaptive Decision Making of “Ablate-and-Wait” Versus Transplantation in Patients With Hepatocellular Carcinoma

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Abstract

Background/Aims:

In patients with early-stage hepatocellular carcinoma (HCC), selection of candidates for liver transplantation (LT) requires refinement based on tumor biology to maximize the outcome. We aimed to prognosticate LT candidates with HCC using a risk prediction model for post-LT recurrence.

Patients and Methods:

A total of 197 consecutive patients were included who underwent LT for hepatitis B-related HCC within the Milan criteria. A risk prediction model was developed for post-LT recurrence using the Cox model and was internally validated.

Results:

Among those undergoing LT as their first HCC treatment (n=70, initial LT group), poor prognosis was associated with maximal tumor size and multinodularity. The remaining 127 patients (deferred LT group) received radiofrequency ablation (n=69) and/or transarterial chemoembolization (n=98) before LT. Multinodularity, maximal tumor size, posttransarterial chemoembolization progressive disease, baseline alpha-fetoprotein, and alpha-fetoprotein difference (between baseline and pre-LT) were incorporated into a risk prediction model for the deferred LT group, which was thereby stratified into low-risk (score<5), intermediate-risk, and high-risk (score≥8) subgroups. Recurrence-free survival was significantly different among the deferred LT prognostic subgroups (P<0.001).

Conclusions:

This risk prediction model may help refinement of “ablate-and-wait” strategy for LT candidates by avoiding LT in those with either high risk score at baseline or increasing score under repeated locoregional therapies.

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