Evidence map›Paper›PMID 29142236›Full record

ArticleScientific reports2017

Circulating miR-210 and miR-22 combined with ALT predict the virological response to interferon-alpha therapy of CHB patients.

Jin Li, Xiaonan Zhang, Liang Chen, Zhanqing Zhang, Jiming Zhang, Weixia Wang, Min Wu, Bisheng Shi, Xinxin Zhang, Maya Kozlowski and 2 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.2field-weighted citation impact, top 20% 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

14 citing papers in PubMed, 18 citations in OpenAlex.

  1. Unifying and unique roles of non-coding RNA biomarkers in liver and heart fibrosis.Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · 2026
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  7. Liver Damage and microRNAs: An Update.Current issues in molecular biology · 2022
    Review
  8. Article
  9. Review
  10. Review
  11. Review
  12. Review
  13. Article
  14. 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

12 authors at 4 institutions in 1 country.

Jin LiResearch Unit, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.
Xiaonan ZhangResearch Unit, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.
Liang ChenDepartment of Hepatology, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.
Zhanqing ZhangDepartment of Hepatology, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.
Jiming ZhangDepartment of Infectious Diseases, Huashan Hospital, Fudan University, Shanghai, China.
Weixia WangResearch Unit, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.
Min WuResearch Unit, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.
Bisheng ShiResearch Unit, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.
Xinxin ZhangInstitute of Infectious and Respiratory Diseases, School of Medicine, Shanghai Jiaotong University, Ruijin Hospital, Shanghai, China.
Maya KozlowskiResearch Unit, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.
Yunwen HuResearch Unit, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China. ywhu0117@126.com.
Zhenghong YuanResearch Unit, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China. zhyuan@shaphc.org.
Shanghai Medical College of Fudan University · CNShanghai Public Health Clinical Center · CNFudan University · CNRuijin Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Interferon-alpha (IFN-α) therapy of chronic hepatitis B (CHB) patients is constrained by limited response and side effects. We described a panel of circulating microRNAs (miRNAs) which could potentially predict outcome of IFN-α therapy. Here, we report development of a simplified scoring model for personalized treatment of CHB patients. 112 CHB patients receiving IFN-α treatment were randomly divided into a training (n = 75) or a validation group (n = 37). The expression of 15 candidate miRNAs was detected in training group with 5 miRNAs exhibiting significantly different levels (p < 0.0001) between early virological response (EVR) and non-early virological response (N-EVR). These 5 miRNAs were further tested in validation phase. Refinement analyses of results from training phase established a model composed of miR-210, miR-22 and alanine aminotransferase (ALT), with area under ROC curve (AUC) of 0.874 and 0.816 in training and validation groups, respectively. In addition, this model showed prognostic value for sustained virological response (SVR) (AUC = 0.821). Collectively, this simplified scoring model composed of miR-210, miR-22 and ALT can reproducibly predict the EVR and SVR of IFN-α therapy in CHB patients. The model should help to forecast the outcome of IFN-α treatment prior to therapy decision involving nucleoside analogs or IFNs.

Indexed as

AdolescentAdultAlanine TransaminaseAntiviral AgentsFemaleHepatitis B, ChronicHepatitis B Surface AntigensHumansInterferon-alphaMaleMicroRNAsMiddle AgedPrecision MedicinePrognosisYoung AdultAlanine TransaminaseAntiviral AgentsHepatitis B Surface AntigensInterferon-alphaMicroRNAsMIRN210 microRNA, humanMIRN22 microRNA, human

Identifiers

PMID29142236
PMCPMC5688172
OpenAlexW2767606769

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.