AFP-L3 and DCP are superior to AFP in predicting waitlist dropout in HCC patients: Results of a prospective study

Neil Mehta1, Prashant Kotwani1, Joshua Norman1

  • 1Division of Gastroenterology, Department of Medicine, University of California, San Francisco, California, USA.

Insights

Alpha-fetoprotein lectin-3 (AFP-L3) and des-gamma-carboxyprothrombin (DCP) predict liver cancer transplant waitlist dropout better than AFP. High levels of both AFP-L3 and DCP indicate a 100% risk of dropout.

Area of Science:

  • Hepatology
  • Oncology
  • Transplantation Medicine

Background:

  • Alpha-fetoprotein (AFP) is a standard biomarker for hepatocellular carcinoma (HCC) prognosis.
  • Novel biomarkers are needed to predict liver transplantation (LT) waitlist dropout in HCC patients.
  • The predictive value of AFP lectin-3 (AFP-L3) and des-gamma-carboxyprothrombin (DCP) for waitlist dropout is currently unknown.

Purpose of the Study:

  • To evaluate the efficacy of AFP, AFP-L3, and DCP as biomarkers for predicting waitlist dropout in HCC patients awaiting LT.
  • To compare the prognostic value of these biomarkers against AFP alone.

Main Methods:

  • Prospective single-center study of 267 HCC patients listed for LT.
  • Measurement of AFP, AFP-L3, and DCP at the time of LT listing.
  • Follow-up for waitlist dropout, LT, or ongoing waitlist status.
  • Cox proportional hazards analysis and Kaplan-Meier survival analysis.

Main Results:

  • AFP-L3 (≥35%) and DCP (≥7.5 ng/mL) were significantly associated with increased waitlist dropout.
  • AFP levels, across tested cutoffs, did not predict waitlist dropout.
  • Multivariable analysis confirmed AFP-L3 and DCP as independent predictors of dropout, alongside time to listing and MELD-Na score.
  • Patients with both AFP-L3 ≥35% and DCP ≥7.5 ng/mL had a 100% probability of waitlist dropout within 2 years.

Conclusions:

  • AFP-L3 and DCP are superior to AFP in predicting waitlist dropout for HCC patients awaiting LT.
  • The combination of elevated AFP-L3 and DCP levels provides significant prognostic value, identifying patients at highest risk of waitlist dropout.

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