Evidence map›Paper›PMID 39702929›Full record

ArticleCancer medicine2024

Gut Microbiota as Mediator and Moderator Between Hepatitis B Virus and Hepatocellular Carcinoma: A Prospective Study.

Bingren Hu, Yi Yang, Jiangqiao Yao, Ganglian Lin, Qikuan He, Zhiyuan Bo, Zhewei Zhang, Anlvna Li, Yi Wang, Gang Chen and 1 more

Abstract read
In one paragraph

Article in Cancer medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 2 pooled it
–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

4 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Review
  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

11 authors.

Bingren HuDepartment of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
Yi YangDepartment of Epidemiology and Biostatistics, School of Public Health, Wenzhou Medical University, Wenzhou, China.
Jiangqiao YaoDepartment of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
Ganglian LinDepartment of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
Qikuan HeDepartment of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.ORCID 0000-0002-7370-1428
Zhiyuan BoDepartment of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
Zhewei ZhangThe First Clinical College, Wenzhou Medical University, Wenzhou, China.
Anlvna LiThe First Clinical College, Wenzhou Medical University, Wenzhou, China.
Yi WangDepartment of Epidemiology and Biostatistics, School of Public Health, Wenzhou Medical University, Wenzhou, China.ORCID 0000-0002-0558-7491
Gang ChenDepartment of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.ORCID 0000-0001-6067-6959
Yunfeng ShanDepartment of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.ORCID 0000-0003-4811-8932

Funding

National Natural Science Foundation of China 82072685
6 · The paper itself

Abstract

backgroundThe impact of gut microbiome on hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) is unclear. We aimed to evaluate the potential correlation between gut microbiome and HBV-related HCC and introduced novel machine learning (ML) signatures based on gut microbe to predict the risk of HCC. MATERIALS AND

methodsA total of 640 patients with chronic liver diseases or HCC were prospectively recruited between 2019 and 2022. Fecal samples were collected and subjected to 16S rRNA gene sequencing. Univariate and multivariate logistic regression was applied to identify risk characteristics. Several ML methods were employed to construct gut microbe-based models and the predictive performance was evaluated.

resultsA total of 571 patients were involved in the study, including 374 patients with HCC and 197 patients with chronic liver diseases. After the propensity score matching method, 147 pairs of participants were enrolled in the analysis. Bacteroidia and Bacteroidales were demonstrated to exert mediating effects between HBV and HCC, and the moderating effects varied across Bacilli, Lactobacillales, Erysipelotrichaceae, Actinomyces, and Roseburia. HBV, alpha-fetoprotein, alanine transaminase, triglyceride, and Child-Pugh were identified as independent risk factors for HCC occurrence. Seven ML-based HBV-gut microbe models were established to predict HCC, with AUCs ranging from 0.821 to 0.898 in the training set and 0.813-0.885 in the validation set. Furthermore, the merged clinical-HBV-gut microbe models exhibited a comparable performance to HBV-gut microbe models.

conclusionsGut microbes are important factors between HBV and HCC through its potential mediating and moderating effects, which can be used as valuable biomarkers for the pathogenesis of HBV-related HCC.

Indexed as

Carcinoma, HepatocellularGastrointestinal MicrobiomeHepatitis B virusLiver NeoplasmsAdultAgedFecesFemaleHepatitis BHumansMachine LearningMaleMiddle AgedProspective StudiesRisk FactorsRNA, Ribosomal, 16SRNA, Ribosomal, 16Sgut‐liver axisgut microbiotahepatitis B virushepatocellular carcinomamachine learning

Identifiers

PMID39702929
PMCPMC11659115

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.