Evidence map›Paper›PMID 32790527›Full record

SynthesisThe Journal of international medical research2020

Association between the interferon-γ +874T/A polymorphism and susceptibility to hepatitis B virus infection: a meta-analysis.

Liang Li

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in The Journal of international medical research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.3field-weighted citation impact, top 40% of its field
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, 3 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. 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

1 author at 1 institution in 1 country.

Liang LiDepartment of Infectious Diseases, Xiangya Hospital Central South University, Changsha, Hunan, China.ORCID https://orcid.org/0000-0002-8739-4393
Central South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study investigated the correlation between the interferon (IFN)-γ +874T/A polymorphism and hepatitis B virus (HBV) susceptibility using meta-analysis.

methodsPubMed, EMBASE, Web of Science, CNKI, and China Wanfang databases were searched for case-control studies investigating the IFN-γ +874T/A polymorphism and HBV susceptibility from the time of database establishment to April 2020. Stata 15.0 software was used, and the subgroups of ethnicity and Hardy-Weinberg equilibrium were analyzed.

resultsThirteen articles were included in this study. Significant differences were seen in the allelic model, dominant model, homozygous model, and heterozygous model, but heterogeneity was high. Analysis of the East Asian population revealed combined odds ratios of the allelic model (T vs. A), dominant model (TT + TA vs. AA), homozygous model (TT vs. AA), and heterozygous model (TA vs. AA) of 0.61, 0.56, 0.50, and 0.59, respectively. The difference was significant and the heterogeneity low. The recessive model showed no significance in the overall comparison, or in East Asian and Caucasian populations.

conclusionsThe IFN-γ +874T/A polymorphism is associated with the risk of HBV, especially in the East Asian population. Individuals with the T allele and TT and TA genotypes have a reduced risk of HBV infection.

Indexed as

Hepatitis BHepatitis B virusChinaGenetic Predisposition to DiseaseHumansInterferon-gammaPolymorphism, Single NucleotideInterferon-gammaEast Asian populationHepatitis B virusinterferon-γmeta-analysispolymorphismT allele

Identifiers

PMID32790527
PMCPMC7427031
OpenAlexW3049416328

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.