Annals of Hepatology (Mar 2023)

O-10 SIMILAR RISK RECLASSIFICATION OF HCC RECURRENCE BETWEEN THE AFP SCORE AND METROTICKET 2.0 AT LISTING AND AT LAST REASSESSMENT

  • Federico Piñero,
  • Charlotte Costentin,
  • Helena Degroote,
  • Quirino Lai,
  • Fernando Rubinstein,
  • Christophe Duvoux

Journal volume & issue
Vol. 28
p. 101020

Abstract

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Introduction and Objectives: Recently, two composite models, the alpha-fetoprotein (AFP) score and the Metroticket 2.0, have been proposed to select patients with hepatocellular carcinoma (HCC) for liver transplantation (LT). This study aimed to compare both models in their predictive performance of post-LT outcomes and their net reclassification of risk of recurrence. Materials and Methods: This multicenter cohort study included 2444 adult patients who underwent LT for HCC in Europe and Latin America. The discrimination power of each model was estimated using adapted Harrell c-statistics and the NRI for recurrence was compared considering each model´s threshold assessed at listing and at last pre-LT reassessment. Results: At listing, although the Metroticket 2.0 showed a higher discrimination power for HCC recurrence compared to the AFP score, no differences were observed comparing each model's thresholds. At the last tumor evaluation, c-statistics did not significantly differ. Overall, predictive gaps and overlaps were observed between the model's thresholds. At listing and at last pre-LT reassessment, the Metroticket 2.0 did not show a significant gain on the NRI. Patients meeting both composite model´s thresholds either within or beyond the Milan criteria showed the lowest risk of HCC recurrence [SHR of 0.28 (95% CI 0.22-0.36; P<.0001)], whereas a higher risk of recurrence was observed in patients exceeding both composite models, even meeting the Milan criteria. Conclusions: the Metroticket 2.0 did not present a gain on risk reclassification of HCC recurrence over the AFP score at the time of listing or at the last tumor reassessment. The combination of these composite models might be a promising clinical approach.