Evidence map›Paper›PMID 27578555›Full record

SynthesisScientific reports2016

TNF-α Promoter Polymorphisms Predict the Response to Etanercept More Powerfully than that to Infliximab/Adalimumab in Spondyloarthritis.

Jing Liu, Zheng Dong, Qi Zhu, Dongyi He, Yanyun Ma, Aiping Du, Fan He, Dongbao Zhao, Xia Xu, Hui Zhang and 2 more

Open access · goldAbstract readMeta-AnalysisReview
In one paragraph

Synthesis in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
2.4field-weighted citation impact, top 12% 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, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Trial
  4. Review
  5. Review
  6. Journal of personalized medicine · 2023
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Review
  13. Review
  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 5 institutions in 1 country.

Jing LiuState Key Laboratory of Genetic Engineering and Ministry of Education (MOE) Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China.
Zheng DongState Key Laboratory of Genetic Engineering and Ministry of Education (MOE) Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China.
Qi ZhuGuanghua Integrative Medicine Hospital, Shanghai, China.
Dongyi HeGuanghua Integrative Medicine Hospital, Shanghai, China.
Yanyun MaState Key Laboratory of Genetic Engineering and Ministry of Education (MOE) Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China.
Aiping DuState Key Laboratory of Genetic Engineering and Ministry of Education (MOE) Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China.
Fan HeState Key Laboratory of Genetic Engineering and Ministry of Education (MOE) Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China.
Dongbao ZhaoDepartment of Rheumatology and Immunology, Changhai Hospital, affiliated to second military medical university, Shanghai, China.
Xia XuDepartment of Rheumatology and Immunology, Changhai Hospital, affiliated to second military medical university, Shanghai, China.
Hui ZhangState Key Laboratory of Genetic Engineering and Ministry of Education (MOE) Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China.
Li JinState Key Laboratory of Genetic Engineering and Ministry of Education (MOE) Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China.
Jiucun WangState Key Laboratory of Genetic Engineering and Ministry of Education (MOE) Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China.
Fudan University · CNState Key Laboratory of Genetic EngineeringShanghai Guanghua Hospital of Integrated Traditional Chinese and Western Medicine · CNChanghai Hospital · CNSecond Military Medical University · CN

Funding

Studies of HLA Region Genomics in Systemic Sclerosis and Ankylosing SpondyilitisU01AI090909 · NIAID · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI MAYES, MAUREEN MAUREEN, REVEILLE, JOHN DUFFIN · 2010 to 2014
$2.9M
NIAID NIH HHS U01 AI090909
6 · The paper itself

Abstract

While previous studies have researched in association analyses between TNFα promoter polymorphisms and responses to TNF blockers in spondyloarthritis patients, their results were conflicting. Therefore, we aimed to determine whether TNFα promoter polymorphisms could predict response to TNF blockers and find the source of heterogeneity. Data were extracted and analyzed from published articles and combined with our unpublished data. We found that the greatest potential sources of heterogeneity in the results were gender ratio, disease type, continents, and TNF blockers. Then Stratification analysis showed that the TNFα -308 G allele and the -238 G allele predicted a good response to TNF blockers (OR = 2.64 [1.48-4.73]; 2.52 [1.46-4.37]). However, G alleles of TNFα -308 and -238 could predict the response to etanercept (OR = 4.02 [2.24-7.23]; 5.17 [2.29-11.67]) much more powerfully than the response to infiliximab/adalimumab (OR = 1.68 [1.02-2.78]; 1.28 [0.57-2.86]). TNFα -857 could not predict the response in either subgroup. Cumulative meta-analysis performed in ankylosing spondylitis patients presented the odds ratio decreased with stricter response criteria. In conclusion, TNFα -308 A/G and -238 A/G are more powerful to predict the response to Etanercept and it is dependent on the criteria of response.

Indexed as

AllelesPolymorphism, GeneticPromoter Regions, GeneticSpondylitis, AnkylosingAdalimumabEtanerceptFemaleHumansInfliximabMalePredictive Value of TestsTumor Necrosis Factor-alphaAdalimumabEtanerceptInfliximabTumor Necrosis Factor-alpha

Identifiers

PMID27578555
PMCPMC5006048
OpenAlexW2511107980

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.