Evidence map›Paper›PMID 24367931›Full record

Trial reportJournal of interferon & cytokine research : the official journal of the International Society for Interferon and Cytokine Research2014

Long-term effect on natural killer cells by interferon-α therapy on the outcomes of HCV infection.

Xiaoli Hu, Yanfang Jiang, Xiurong Li, Yanhang Gao, Xiaoli Guo, Xiumei Chi, Hongqing Yan, Junyan Feng, Jin Zhong, Bing Sun and 4 more

Open access · greenAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Journal of interferon & cytokine research : the official journal of the International Society for Interferon and Cytokine Research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.6field-weighted citation impact, top 33% 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

6 citing papers in PubMed, 7 citations in OpenAlex.

  1. NKp30Scientific reports · 2016
    Trial
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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

14 authors at 4 institutions in 3 countries.

Xiaoli Hu1 Department of Hepatology, The First Hospital, Jilin University , Changchun, China .
Yanfang Jiang
Xiurong Li
Yanhang Gao
Xiaoli Guo
Xiumei Chi
Hongqing Yan
Junyan Feng
Jin Zhong
Bing Sun
Xue Shao
Weihua Xiao
Yu Pan
Junqi Niu
Jilin University · CNInstitut Pasteur · FRHeilongjiang Provincial Hospital · CNUniversity of Science and Technology of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Natural killer (NK) cells act as innate immune cells against hepatitis C virus (HCV) infection. Interferon-α (IFN-α) and ribavirin are the standard treatments for patients with HCV infection. This study is aimed at investigating the dynamic changes in the frequency of different subsets of NK cells following treatment in xx chronic hepatitis C (CHC) patients. CHC patients were treated with peg-IFN or IFN-α, and followed up for 72 weeks. The frequency of different subsets of NK in CHC patients was determined longitudinally by flow cytometry. Treatment with the standard therapy increased the percentages of NKp30(+), NKp46(+), and CD107a(+) NK cells, which were positively correlated with the declining of serum HCV-RNA, but not IFN-γ(+) NK cells. NKG2A(+) and KIR2DL3(+) NK cells were associated with an early virological response in CHC patients. Treatment with IFN-α adjusts the balance of activated receptors and inhibitory receptors and enhances the cytotoxic activity of NK cells. Therefore, measuring NK subsets may be valuable for therapeutic responses in CHC patients.

Indexed as

AdultFemaleFlow CytometryHepacivirusHepatitis C, ChronicHumansInterferon-alphaKiller Cells, NaturalMaleMiddle AgedTime FactorsTreatment OutcomeInterferon-alpha

Identifiers

PMID24367931
PMCPMC4015508
OpenAlexW1132160997

What OpenQuestion holds

Textmetadata
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.