Evidence map›Paper›PMID 39569574›Full record

ArticleAlimentary pharmacology & therapeutics2025

Development and Validation of a PIVKA-II-Based Model for HCC Risk Stratification in Patients With HCV-Related Cirrhosis Successfully Treated With DAA.

Gian Paolo Caviglia, Piero Fariselli, Roberta D'Ambrosio, Piero Colombatto, Elisabetta Degasperi, Gabriele Ricco, Maria Lorena Abate, Giovanni Birolo, Giulia Troshina, Francesco Damone and 8 more

Abstract readValidation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Alimentary pharmacology & therapeutics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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.

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Observational
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4 · The record

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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

18 authors.

Gian Paolo CavigliaDepartment of Medical Sciences, Liver Unit, University of Turin, Turin, Italy.
Piero FariselliDepartment of Medical Sciences, Computational Biomedicine, University of Turin, Turin, Italy.
Roberta D'AmbrosioDivision of Gastroenterology and Hepatology, Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
Piero ColombattoHepatology Unit and Laboratory of Molecular Genetics and Pathology of Hepatitis Viruses, Reference Center of the Tuscany Region for Chronic Liver Disease and Cancer, University Hospital of Pisa, Pisa, Italy.
Elisabetta DegasperiDivision of Gastroenterology and Hepatology, Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.ORCID https://orcid.org/0000-0002-9899-4669
Gabriele RiccoHepatology Unit and Laboratory of Molecular Genetics and Pathology of Hepatitis Viruses, Reference Center of the Tuscany Region for Chronic Liver Disease and Cancer, University Hospital of Pisa, Pisa, Italy.
Maria Lorena AbateDepartment of Medical Sciences, Liver Unit, University of Turin, Turin, Italy.
Giovanni BiroloDepartment of Medical Sciences, Computational Biomedicine, University of Turin, Turin, Italy.
Giulia TroshinaDepartment of Medical Sciences, Liver Unit, University of Turin, Turin, Italy.
Francesco DamoneHepatology Unit and Laboratory of Molecular Genetics and Pathology of Hepatitis Viruses, Reference Center of the Tuscany Region for Chronic Liver Disease and Cancer, University Hospital of Pisa, Pisa, Italy.
Barbara CocoHepatology Unit and Laboratory of Molecular Genetics and Pathology of Hepatitis Viruses, Reference Center of the Tuscany Region for Chronic Liver Disease and Cancer, University Hospital of Pisa, Pisa, Italy.
Daniela CavalloneHepatology Unit and Laboratory of Molecular Genetics and Pathology of Hepatitis Viruses, Reference Center of the Tuscany Region for Chronic Liver Disease and Cancer, University Hospital of Pisa, Pisa, Italy.
Riccardo PerbelliniDivision of Gastroenterology and Hepatology, Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
Sara MonicoDivision of Gastroenterology and Hepatology, Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
Giorgio Maria SaraccoDepartment of Medical Sciences, Liver Unit, University of Turin, Turin, Italy.
Maurizia Rossana BrunettoHepatology Unit and Laboratory of Molecular Genetics and Pathology of Hepatitis Viruses, Reference Center of the Tuscany Region for Chronic Liver Disease and Cancer, University Hospital of Pisa, Pisa, Italy.
Pietro LamperticoDivision of Gastroenterology and Hepatology, Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.ORCID https://orcid.org/0000-0002-1026-7476
Alessia CiancioDepartment of Medical Sciences, Liver Unit, University of Turin, Turin, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

aimsPatients with hepatitis C virus (HCV)-related cirrhosis with sustained virological response (SVR) to direct-acting antivirals (DAA) remain at risk of developing hepatocellular carcinoma (HCC). Recently, serum protein induced by vitamin K absence or antagonist-II (PIVKA-II) has shown promising results as an HCC-predictive biomarker. We aimed to develop and validate a PIVKA-II-based model for HCC risk stratification in cirrhotic patients with SVR to DAA.

methodsA total of 1220 consecutive patients (Turin, n = 531; Pisa, n = 335; Milan, n = 354) with HCV-related cirrhosis treated with DAA were included in the study. Patients were retrospectively allocated to the training cohort (Turin+Pisa; median follow-up [FU] 39, 22-55 months; incident HCC: 93 [10.7%]) and validation cohort (Milan; median FU 49.0, 35.0-52.0 months; incident HCC: 19 [5.4%]). Serum PIVKA-II levels were measured using the LumipulseG system (Fujirebio, Japan) at SVR12 (Turin and Pisa cohorts) or the end of treatment (Milan cohort).

resultsUsing Cox regression analysis, a model including PIVKA-II combined with age, sex, ALT, AST, γGT, platelet count, albumin and total bilirubin was derived from the training cohort (C-index = 0.72). In the validation cohort, the model showed a C-index of 0.71 with an area under the curve of 0.84 for identifying patients who developed HCC during the first 12 months of FU. When patients were grouped into three risk categories, the cumulative incidence of HCC was 2.7%, 4.0% and 14.3% in the low-, medium- and high-risk groups, respectively (p < 0.001). Notably, no HCC occurred within 3 years of FU in the low-risk group.

conclusionsOur PIVKA-II-based model showed satisfactory accuracy for HCC risk stratification and may represent a valuable tool for implementing risk-based surveillance protocols in patients with HCV-related cirrhosis with SVR to DAA.

Indexed as

Antiviral AgentsBiomarkersCarcinoma, HepatocellularLiver CirrhosisLiver NeoplasmsProtein PrecursorsProthrombinSustained Virologic ResponseAgedFemaleHepatitis C, ChronicHumansMaleMiddle AgedRetrospective StudiesRisk AssessmentacarboxyprothrombinAntiviral AgentsBiomarkersProtein PrecursorsProthrombinbiomarkersDAAHCChepatitis Cnon‐invasive tests

Identifiers

PMID39569574
PMCPMC11707638

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