Evidence map›Paper›PMID 41935630›Full record

ArticleJHEP reports : innovation in hepatology2026

IMAT-HCC model: Liver stiffness-enhanced integrated risk stratification for HCC recurrence after resection.

Matteo Serenari, Matteo Cescon, Chiara Bonatti, Bernardo Stefanini, Edoardo Prosperi, Elton Dajti, Francesco Tovoli, Matteo Ravaioli, Fabio Piscaglia, Federico Ravaioli

Abstract read
In one paragraph

Article in JHEP reports : innovation in hepatology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Matteo SerenariHepato-biliary and Transplant Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy; Department of Medical and Surgical Sciences (DIMEC), University of Bologna, Bologna, Italy.
Matteo CesconHepato-biliary and Transplant Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy; Department of Medical and Surgical Sciences (DIMEC), University of Bologna, Bologna, Italy.
Chiara BonattiHepato-biliary and Transplant Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy; Department of Medical and Surgical Sciences (DIMEC), University of Bologna, Bologna, Italy.
Bernardo StefaniniDepartment of Medical and Surgical Sciences (DIMEC), University of Bologna, Bologna, Italy; Division of Internal Medicine, Hepatobiliary and Immunoallergic Diseases, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
Edoardo ProsperiHepato-biliary and Transplant Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy; Department of Medical and Surgical Sciences (DIMEC), University of Bologna, Bologna, Italy.
Elton DajtiGastroenterology Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
Francesco TovoliDepartment of Medical and Surgical Sciences (DIMEC), University of Bologna, Bologna, Italy; Division of Internal Medicine, Hepatobiliary and Immunoallergic Diseases, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
Matteo RavaioliHepato-biliary and Transplant Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy; Department of Medical and Surgical Sciences (DIMEC), University of Bologna, Bologna, Italy.
Fabio PiscagliaDepartment of Medical and Surgical Sciences (DIMEC), University of Bologna, Bologna, Italy; Division of Internal Medicine, Hepatobiliary and Immunoallergic Diseases, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
Federico RavaioliDepartment of Medical and Surgical Sciences (DIMEC), University of Bologna, Bologna, Italy; Division of Internal Medicine, Hepatobiliary and Immunoallergic Diseases, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy. Electronic address: f..ravaioli@unibo.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND &

aimsEarly enthusiasm for adjuvant immunotherapy with atezolizumab plus bevacizumab after curative treatment of hepatocellular carcinoma (HCC) has been tempered by longer follow-up, which questioned the durability of benefit. Beyond treatment efficacy, inadequate patient selection may have contributed. We aimed to externally validate the high-risk criteria adopted in the IMbrave050 trial and to investigate whether integrating liver stiffness measurement (LSM) could improve recurrence risk stratification and provide a pragmatic framework for future adjuvant trial enrolment.

methodsWe retrospectively analysed 147 patients who underwent curative liver resection for HCC between 2010 and 2020 at our institution. High-risk status was defined by IMbrave050 criteria. LSM was assessed preoperatively. Competing-risk analyses (Fine-Gray) evaluated predictors of recurrence and liver-related outcomes; we quantified the added value of LSM using category-based net reclassification improvement. We then defined an integrated selection rule (Integrated Model for Adjuvant Trial Selection in Hepatocellular Carcinoma [IMAT-HCC]) as IMbrave050-IN or IMbrave050-OUT with LSM ≥15 kPa.

resultsOver a median 34 months, 88/147 patients (59.9%) recurred. Both IMbrave050 high-risk features and LSM ≥15 kPa were independently associated with recurrence (subhazard ratio [SHR] 1.66, 95% CI 1.09-2.54; and SHR 1.62, 95% CI 1.07-2.47, respectively). Patients classified as IMbrave050-OUT but with LSM ≥15 kPa showed recurrence rates comparable to IMbrave050-IN patients, whereas those with LSM <15 kPa had substantially lower risk. The IMAT-HCC rule provided clearer separation of cumulative incidence functions than IMbrave050 alone and improved patient reclassification (overall net reclassification improvement 8.0%), driven by correct up-classification of patients who eventually recurred.

conclusionIntegrating LSM into tumour-based risk criteria refines identification of biologically high-risk patients after resection and improves exclusion of truly low-risk individuals. IMAT-HCC represents a simple, non-invasive and trial-ready selection rule that may enhance enrichment strategies for future adjuvant trials in HCC. IMPACT AND IMPLICATIONS: This study demonstrates that integrating liver stiffness measurement with tumour-based criteria refines the identification of patients at high biological risk of recurrence after curative resection for hepatocellular carcinoma. By addressing the limitations of purely tumour-centric selection strategies (i.e. IMbrave050 criteria), it highlights the prognostic relevance of the underlying liver disease in shaping post-resection outcomes. Incorporation of this approach into clinical research and trial design could improve risk stratification and patient selection for adjuvant therapies, while avoiding overgeneralisation given the retrospective, single-centre nature of the study.

Indexed as

Carcinoma, HepatocellularLiverLiver NeoplasmsNeoplasm Recurrence, LocalAgedElasticity Imaging TechniquesFemaleHepatectomyHumansMaleMiddle AgedPatient SelectionRetrospective StudiesRisk AssessmentHepatectomyHepatocellular carcinomaLiver stiffnessNeoadjuvant therapy

Identifiers

PMID41935630
PMCPMC13158403

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