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Aim Discordance between pre- LT imaging and explanted liver findings have been reported after liver transplantation ( LT) for hepatocellular carcinoma ( HCC), suggesting the need of reassessing the risk of HCC recurrence post- LT. Our aims were to compare pre- LT imaging and explants features and to test the performances of four explant-based predictive models of recurrence in an external cohort. Methods Staging according to pre- LT imaging and explant features were compared. Four explants-based models were retrospectively tested in a cohort of 372 patients transplanted for HCC in 19 French centres between 2003 and 2005. Accuracies of the scores were compared. Results Pre- LT imaging underestimated tumour burden in 83 (22.7%) patients according to Milan criteria. The highest AUCs for prediction of 5-years recurrence were observed in the 'Up to seven' (0.7915 [95% CI: 0.7339-0.849]) and Decaens models (0.747 [95% CI: 0.6877-0.806]), with two levels of risk: low (10%) and high (>50%). Chan and Iwatsuki models identified 3 and 4 levels of risk, but had lower AUCs (0.68 and 0.70) respectively. Accuracy of the 'Up to seven' model was superior to the Decaens model ( P=.034), which was superior to the Chan model ( P=.0041) but not to the Iwatsuki model ( P=.17). Conclusion Pre- LT imaging underestimates tumour burden, and prediction of recurrence should be reassessed after LT. The explant-based 'Up to seven' and Decaens models provided the best accuracy for prediction of 5-year recurrence, identifying only two levels of risk. New models are needed to further refine the prediction of recurrence after LT. [ABSTRACT FROM AUTHOR]

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 log10 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. [ABSTRACT FROM AUTHOR]