Evidence map›Paper›PMID 42008824›Full record

ArticleHepatology (Baltimore, Md.)2026

Development and validation of risk stratification models for hepatocellular cancer: A framework from the translational liver cancer consortium.

Fasiha Kanwal, Ziding Feng, Yujin Hoshida, Jagpreet Chhatwal, Vincent Wai-Sun Wong, George N Ioannou, Pierre Nahon, William Lotter, Jing Ning, Bachir Taouli and 3 more

Abstract read
In one paragraph

Article in Hepatology (Baltimore, Md.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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.

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

1 citing paper in PubMed.

  1. Validation of Risk Models for Predicting Post-SVR HCC in Real-World Surveillance Across Global Geographic Regions.Liver international : official journal of the International Association for the Study of the Liver · 2026
    Article
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

13 authors.

Fasiha KanwalDepartment of Medicine and the Institute of Clinical and Translational Research, Baylor College of Medicine, Houston, Texas, USA.ORCID 0000-0001-6715-3966
Ziding FengPublic Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA.
Yujin HoshidaDepartment of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Jagpreet ChhatwalCenter for Health Technology Assessment, Mass General Brigham, Harvard Medical School, Boston, Massachusetts, USA.ORCID 0000-0001-8741-4430
Vincent Wai-Sun WongMedical Data Analytics Center, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China.ORCID 0000-0003-2215-9410
George N IoannouDivision of Gastroenterology and Hepatology, Veterans Affairs Puget Sound Health Care System and University of Washington, Seattle, Washington, USA.
Pierre NahonAP-HP, Hôpitaux Universitaires Paris Seine Saint-Denis, Liver Unit, Bobigny, France.
William LotterDepartment of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts, USA.ORCID 0000-0002-9427-8833
Jing NingDepartment of Biostatistics, MD Anderson Cancer Center, Houston, Texas, USA.ORCID 0000-0002-5289-331
Bachir TaouliDepartment of Diagnostic, Molecular, and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Guillermo MarquezDivision of Cancer Prevention, Cancer Biomarker Branch, National Cancer Institute, Rockville, Maryland, USA.
Sidney W FuDivision of Cancer Prevention, Cancer Biomarker Branch, National Cancer Institute, Rockville, Maryland, USA.ORCID 0000-0002-2945-4183
Amit G SingalDepartment of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA.ORCID 0000-0002-1172-3971

Funding

The Early Detection Research Network: Data Management and Coordinating CenterU24CA086368 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI RUTH D ETZIONI, Ziding Feng · 2010 to 2026
$75.7M
Prevention of Hepatocellular Carcinoma Related to Metabolic SyndromeP01CA263025 · NCI · BAYLOR COLLEGE OF MEDICINE · PI Christopher I. Amos · 2022 to 2026
$8.9M
UT Southwestern Liver Cancer SPOREP50CA295495 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI Yujin Hoshida, Amit Singal · 2025 to 2026
$7.5M
Risk Stratification for and Early Detection of Liver CancerU01CA230997 · NCI · BAYLOR COLLEGE OF MEDICINE · PI Jagpreet Chhatwal, Hashem B El-Serag · 2018 to 2026
$6.4M
Consortium on Translational Research in Early Detection of Liver Cancer:Data Management and Coordinating Center (DMCC)U24CA230144 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Ziding Feng · 2018 to 2026
$5.8M
Clinical Validation Center for Hepatocellular CarcinomaU01CA271887 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI FASIHA KANWAL, JORGE A MARRERO · 2022 to 2026
$4.7M
Precision Risk Stratification and Screening for HCC among Patients with Indeterminate Liver NodulesU01CA283935 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI HOSHIDA, YUJIN, SINGAL, AMIT · 2023 to 2025
$3.9M
Reverse-engineering precision liver cancer chemopreventionR01CA233794 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI HOSHIDA, YUJIN · 2019 to 2023
$3.5M
Multi-level Evaluation of Racial/ethnic Disparities in Liver Disease OutcomesR01CA256977 · NCI · BAYLOR COLLEGE OF MEDICINE · PI KANWAL, FASIHA, SINGAL, AMIT · 2021 to 2025
$3.0M
Non-invasive etiology-adjusted precision liver cancer risk predictionR01CA292930 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI HOSHIDA, YUJIN · 2025 to 2025
$2.9M
Accelerating biomarker development through novel statistical methods for analyzing phase III/IV studiesR01CA277133 · NCI · FRED HUTCHINSON CANCER CENTER · PI Ying Huang · 2023 to 2026
$1.6M
Therapeutic modulation of a proteomic HCC risk signature with statins in patients with liver cirrhosisU01CA288375 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI CHUNG, RAYMOND T, DIEHL, ANNA MAE ELIZABETH · 2023 to 2025
$1.3M
NCI NIH HHS P01 CA263025NCI NIH HHS P50 CA295495NCI NIH HHS R01 CA233794NCI NIH HHS R01 CA256977NCI NIH HHS R01 CA277133NCI NIH HHS R01 CA292930NCI NIH HHS U01 CA230997NCI NIH HHS U01 CA271887NCI NIH HHS U01 CA283935NCI NIH HHS U01 CA288375NCI NIH HHS U24 CA086368NCI NIH HHS U24 CA230144
6 · The paper itself

Abstract

Clinical practice guidelines recommend hepatocellular cancer (HCC) surveillance in patients with cirrhosis from any etiology and those with chronic hepatitis B virus (HBV) infection and additional risk factors. However, HCC incidence varies across groups. Several risk stratification models using clinical factors and/or biomarkers have been derived to facilitate tailored HCC surveillance. Although risk stratification models are used for patients with hepatitis B, few have been sufficiently validated in patients with cirrhosis. Indeed, many unanswered questions related to the development, validation, and impact evaluation of risk stratification models must be addressed before widespread implementation can be recommended. The National Cancer Institute's Translational Liver Cancer (TLC) Consortium was established to advance research focused on risk stratification and early detection of liver cancer. The TLC convened a multidisciplinary group, including clinicians, scientists, biostatisticians, and technology experts from the United States, Asia, and Europe, to provide a framework for the development, validation, and implementation of risk stratification models. The framework defines 4 phases of risk stratification model development and validation: phase 1-development and internal validation, phase 2-decision rule development, phase 3-external validation, and phase 4-impact evaluation. The group also defined a set of recommendations to improve the rigor of development and validation of HCC risk stratification strategies. This framework can inform best practices and highlight necessary steps for endorsement by practice guidelines and regulatory agencies, highlighting a path toward implementation in clinical practice.

Indexed as

cirrhosisguidancehepatitis Brisk-stratified screening

Identifiers

PMID42008824
PMCPMC13435454

What OpenQuestion holds

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Registered trials

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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.