Liver transplantation for hepatocellular carcinoma: a model including α-fetoprotein improves the performance of Milan criteria.

Background & Aims: The aim of this study was to generate an improved prognostic model for predicting recurrence in liver transplant candidates with hepatocellular carcinoma (HCC).
Methods: Predictors of recurrence were tested by a Cox model analysis in a training cohort of 537 patients transplanted for HCC. A prognostic score was developed and validated in a national cohort of 435 patients followed up prospectively.
Results: α-Fetoprotein (AFP) independently predicted tumor recurrence and correlated with vascular invasion and differentiation. At a Cox score threshold of 0.7 (area under the receiver operating characteristic curve, 0.701; 95% confidence interval, 0.63-0.76; accuracy, 75.8%), a model combining log(10) AFP, tumor size, and number was highly predictive of tumor recurrence and death. By using a simplified version of the model, with untransformed AFP values, a cut-off value of 2 was identified. In the validation cohort, a score greater than 2 predicted a marked increase in 5-year risk of recurrence (50.6% ± 10.2% vs 8.8% ± 1.7%; P < .001) and decreased survival (47.5% ± 8.1% vs 67.8% ± 3.4%; P = .002) as compared with others. Among patients exceeding Milan criteria, a score of 2 or lower identified a subgroup of patients with AFP levels less than 100 ng/mL with a low 5-year risk of recurrence (14.4% ± 5.3% vs 47.6% ± 11.1%; P = .006). Among patients within Milan criteria, a score greater than 2 identified a subgroup of patients with AFP levels greater than 1000 ng/mL at high risk of recurrence (37.1% ± 8.9% vs 13.3% ± 2.0%; P < .001). Net reclassification improvement showed that predictability of the AFP model was superior to Milan criteria.
Conclusions: Prediction of tumor recurrence is improved significantly by a model that incorporates AFP. We propose the adoption of new selection criteria for HCC transplant candidates, taking into account AFP.
(Copyright © 2012 AGA Institute. Published by Elsevier Inc. All rights reserved.)