HepatoPredict Prognostic Tool for the Decision of Liver Transplant in Hepatocellular Carcinoma (HepatoPredict)

  • STATUS
    Recruiting
  • End date
    Dec 31, 2029
  • participants needed
    40
  • sponsor
    Centro Hospitalar de Lisboa Central
Updated on 14 June 2022

Summary

Liver transplant is the most effective treatment for hepatocellular carcinoma (HCC) in cirrhosis. Due to organs shortage, the proper selection of patients is imperative. Prevailing clinical morphological models used in most centres (Milan Criteria), can exclude potential candidates and include patients with aggressive biological behaviour. To more accurately select candidates for liver transplant, the inclusion of criteria that could predict the behaviour and aggressiveness of tumours, such as molecular markers, might be useful.

The investigators propose the use of a new algorithm (HepatoPredict Prognostic Tool), that combine clinical and molecular criteria that address the biology of tumours, in a single centre prospective, intervention study. Data from the "HepatoPredict genomic signature" are added to the clinical and imagiology algorithm. Based on this tool, patients outside the usual eligibility criteria for liver transplant will be proposed for this treatment. These patients will be transplanted with marginal livers or with livers from patients with Familial Amyloid Polyneuropathy, not competing with patients on the waiting list. Patients will be followed up to 60 months after transplant, to assess survival and HCC recurrence with biannual imagiology screening. Survival and disease-free-survival rates will be compared with those obtained by the usual management of patients included and excluded by Milan Criteria.

Description

Liver transplant is the most effective treatment for hepatocellular carcinoma (HCC) in cirrhosis. Due to organs shortage, the proper selection of patients is imperative. Prevailing clinical morphological models used in most centres (Milan Criteria), can exclude potential candidates and include patients with aggressive biological behaviour. To more accurately select candidates for liver transplant, the inclusion of criteria that could predict the behaviour and aggressiveness of tumours, such as molecular markers, might be useful. The investigators propose the use of a new algorithm (HepatoPredict Prognostic Tool, Ophiomics), combining morphologic information, clinical and molecular criteria, in a prospective, intervention, single centre study.

Patients aged 18 to 70 years, with HCC in cirrhosis, not eligible for liver transplant under the "Milan Criteria", whom had the following morphologic characteristics: total tumour volume below 500 cm3, total number of tumour lesions below 10 and maximum individual tumour diameter below 10 cm, will be proposed for the "HepatoPredict genomic signature" analysis (Ophiomics), obtained from DNA of tumor samples. Those considered candidates by the algorithm are to be proposed for transplant with marginal livers or with livers from patients with Familial Amyloid Polyneuropathy.

Patients will be followed up to 60 months after transplant, to assess survival and HCC recurrence with biannual imagiology screening by triphasic CT scan. Additionally, circulating tumour DNA will be assessed previously to the transplant and biannually for up to 60 months. Survival and disease-free-survival rates will be compared with those obtained with the usual management of patients included and excluded by Milan Criteria, both in the same referral transplant center and in the published literature.

Details
Condition Hepatocellular Carcinoma, Scirrhous, Recurrence Tumor
Treatment Liver Transplant
Clinical Study IdentifierNCT04499833
SponsorCentro Hospitalar de Lisboa Central
Last Modified on14 June 2022

Eligibility

Yes No Not Sure

Inclusion Criteria

Hepatocellular carcinoma associated with cirrhosis
Ages between 18 and 70 years
Total tumour volume below 500 cm3
Total number of tumour lesions below 10
Maximum individual tumour diameter below 10 cm

Exclusion Criteria

eligible under the "Milan Criteria
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