Evidence map›Paper›PMID 40087922›Full record

ArticleLiver international : official journal of the International Association for the Study of the Liver2025

Behaviour-Based Predictive Scores of Hepatocellular Carcinoma in People With Chronic Hepatitis B (ANRS CO22 HEPATHER).

Clémence Ramier, Camelia Protopopescu, Vincent Di Beo, Lucia Parlati, Fabienne Marcellin, Fabrice Carrat, Tarik Asselah, Marc Bourlière, Patrizia Carrieri, ANRS/AFEF CO22 HEPATHER Study Group

Abstract read
In one paragraph

Article in Liver international : official journal of the International Association for the Study of the Liver, 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.

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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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.

Clémence RamierAix Marseille Univ, INSERM, IRD, SESSTIM, Sciences Économiques and Sociales de la Santé and Traitement de l'Information Médicale, Marseille, France.ORCID 0000-0002-1928-0263
Camelia ProtopopescuAix Marseille Univ, INSERM, IRD, SESSTIM, Sciences Économiques and Sociales de la Santé and Traitement de l'Information Médicale, Marseille, France.ORCID 0000-0003-0164-7917
Vincent Di BeoAix Marseille Univ, INSERM, IRD, SESSTIM, Sciences Économiques and Sociales de la Santé and Traitement de l'Information Médicale, Marseille, France.
Lucia ParlatiDépartement d'Hépatologie/Addictologie, Université de Paris Cité; INSERM U1016, AP-HP, Hôpital Cochin, Paris, France.ORCID 0000-0003-1939-5607
Fabienne MarcellinAix Marseille Univ, INSERM, IRD, SESSTIM, Sciences Économiques and Sociales de la Santé and Traitement de l'Information Médicale, Marseille, France.ORCID 0000-0001-8853-3829
Fabrice CarratInstitut National de la Santé et de la Recherche Médicale (INSERM), Institut Pierre Louis d'Epidémiologie et de Santé Publique, Sorbonne Université, Paris, France.
Tarik AsselahDepartment of Hepatology, Centre de Recherche Sur l'Inflammation, INSERM UMR 1149, Hôpital Beaujon, Université de Paris-Cité, Clichy, France.ORCID 0000-0002-0024-0595
Marc BourlièreAix Marseille Univ, INSERM, IRD, SESSTIM, Sciences Économiques and Sociales de la Santé and Traitement de l'Information Médicale, Marseille, France.
Patrizia CarrieriAix Marseille Univ, INSERM, IRD, SESSTIM, Sciences Économiques and Sociales de la Santé and Traitement de l'Information Médicale, Marseille, France.
ANRS/AFEF CO22 HEPATHER Study Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

aimsEarly assessment of hepatocellular carcinoma (HCC) risk could improve long-term outcomes in people with chronic hepatitis B virus (HBV) infection. Some existing HCC predictive scores are not easily implementable. We developed easy-to-use HCC predictive scores based on behavioural and routine bio-clinical data in people with chronic HBV infection.

methodsEight-year follow-up data was analysed from people with chronic HBV infection enrolled in the French ANRS CO22 HEPATHER cohort. Patients were randomly split into two samples (training/testing). A multivariable Cox model for time to HCC was estimated on the training sample. The HCC predictive score was computed by summing the points assigned to model predictors, normalising their coefficients over a 10-year age increment, and rounding to the nearest integer. The Youden index identified the score's optimal risk threshold. Comparisons with existing predictive scores were performed on the testing sample.

resultsIn the study population (N = 4370; 63% of men; 65% of < 50 years old), 56 HCC cases occurred during 25,900 follow-up person-years. Two HCC predictive scores were defined: SADAPTT (daily soft drink consumption, age, hepatitis Delta infection, unhealthy alcohol use, platelet count, heavy tobacco smoking, and HBV treatment) and ADAPTT (the same predictors except for daily soft drink consumption), with ranges 0-13 and 0-14, respectively, and values ≥ 3 indicating a high HCC risk. Their performances were similar to existing scores.

conclusionsWe developed two effective behaviour-based HCC predictive scores, implementable in many settings, including primary care and decentralised areas. Further studies are needed to validate these scores in other datasets.

Indexed as

Carcinoma, HepatocellularHepatitis B, ChronicLiver NeoplasmsAdultAge FactorsAlcohol DrinkingFemaleFollow-Up StudiesFranceHumansMaleMiddle AgedMultivariate AnalysisPredictive Value of TestsProportional Hazards ModelsRisk Assessmentalcoholhepatitis Bhepatitis Deltaliver cancersoft drinktobacco

Identifiers

PMID40087922
PMCPMC11909585

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.