Evidence map›Paper›PMID 31015392›Full record

ArticleAnnals of transplantation2019

Role of Allelic Imbalance in Predicting Hepatocellular Carcinoma (HCC) Recurrence Risk After Liver Transplant.

Duilio Pagano, Floriana Barbera, Pier Giulio Conaldi, Aurelio Seidita, Fabrizio Di Francesco, Daniele Di Carlo, Marco Bàrbara, Fabio Tuzzolino, Angelo Luca, Salvatore Gruttadauria

Open access · hybridAbstract read
In one paragraph

Article in Annals of transplantation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.1field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 1 institution in 1 country.

Duilio PaganoDepartment for Treatment and Study of Abdominal Diseases and Abdominal Transplantation, Mediterranean Institute for Transplantation and High Specialization Therapies (IRCCS-ISMETT), Palermo, Italy.
Floriana BarberaDepartment of Laboratory Medicine and Advanced Biotechnologies, Mediterranean Institute for Transplantation and High Specialization Therapies (IRCCS-ISMETT), Palermo, Italy.
Pier Giulio ConaldiDepartment of Laboratory Medicine and Advanced Biotechnologies, Mediterranean Institute for Transplantation and High Specialization Therapies (IRCCS-ISMETT), Palermo, Italy.
Aurelio SeiditaDepartment for Treatment and Study of Abdominal Diseases and Abdominal Transplantation, Mediterranean Institute for Transplantation and High Specialization Therapies (IRCCS-ISMETT), Palermo, Italy.
Fabrizio Di FrancescoDepartment for Treatment and Study of Abdominal Diseases and Abdominal Transplantation, Mediterranean Institute for Transplantation and High Specialization Therapies (IRCCS-ISMETT), Palermo, Italy.
Daniele Di CarloDepartment for Treatment and Study of Abdominal Diseases and Abdominal Transplantation, Mediterranean Institute for Transplantation and High Specialization Therapies (IRCCS-ISMETT), Palermo, Italy.
Marco BàrbaraDepartment for Treatment and Study of Abdominal Diseases and Abdominal Transplantation, Mediterranean Institute for Transplantation and High Specialization Therapies (IRCCS-ISMETT), Palermo, Italy.
Fabio TuzzolinoResearch Office, Mediterranean Institute for Transplantation and High Specialization Therapies (IRCCS-ISMETT), Palermo, Italy.
Angelo LucaDepartment of Diagnostic and Therapeutic Services, Mediterranean Institute for Transplantation and High Specialization Therapies (IRCCS-ISMETT), Palermo, Italy.
Salvatore GruttadauriaDepartment for Treatment and Study of Abdominal Diseases and Abdominal Transplantation, Mediterranean Institute for Transplantation and High Specialization Therapies (IRCCS-ISMETT), Palermo, Italy.
Istituto Mediterraneo per i Trapianti e Terapie ad Alta Specializzazione · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND One of the most controversial problems for liver transplantation in patients affected by hepatocellular carcinoma (HCC) remains the lack of an oncologic staging system to predict cancer recurrence after liver transplantation (LT). We analyzed allelic imbalance (AI) in 19 microsatellites, and assessed the post-LT HCC recurrence risk. MATERIAL AND METHODS Seventy-one patients were included; 18 had tumor recurrence within 5 years post-transplant. Molecular analysis was done in the primary HCC and peripheral blood samples: a total of 19 microsatellites was used to assess AI. Specific AI was evaluated when outside of range value between 0.66 and 1.5. Based on data in the literature, we grouped the 19 microsatellites into 4 panels. We calculated the fractional allelic imbalance (FAI) to make comparisons between different panels including different subsets of microsatellites. RESULTS We report that AI was associated with HCC recurrence in 3 main loci (D3S2303, D9S251, and D9S254). Tumor recurrence was associated only with 2 specific panels with 9 microsatellites previously reported to be associated with high risk for HCC recurrence. Our data show that fractional allelic imbalance (FAI) index has good negative ability to predict HCC recurrence (Panel 2: negative predictive value of 95%). CONCLUSIONS AI analysis could have prognostic value in risk management of HCC recurrence after LT, especially for early recurrence.

Indexed as

Allelic ImbalanceLiver TransplantationAgedCarcinoma, HepatocellularFemaleHumansLiver NeoplasmsMaleMiddle AgedNeoplasm Recurrence, LocalPrognosisRetrospective StudiesRisk FactorsTreatment Outcome

Identifiers

PMID31015392
PMCPMC6500106
OpenAlexW2941949551

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.