Evidence map›Paper›PMID 26064250›Full record

ArticleInternational journal of clinical and experimental medicine2015

STAT4 polymorphisms and diabetes risk: a meta-analysis with 18931 patients and 23833 controls.

Jian Yi, Xin Fang, Youyun Wan, Juan Wei, Jianjun Huang

Abstract read
In one paragraph

Article in International journal of clinical and experimental medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–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

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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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Central-European journal of immunology · 2020
    Article
  4. Type 1 diabetes: genes associated with disease development.Central-European journal of immunology · 2020
    Review
  5. Article
  6. Article
  7. Central-European journal of immunology · 2016
    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

5 authors.

Jian YiDepartment of Endocrinology, The Ninth Hospital of Wuhan City Wuhan 430060, P. R. China.
Xin FangDepartment of Geriatrics, Union Hospital, Huazhong University of Science and Technolgy Wuhan 430022 , P. R. China.
Youyun WanDepartment of Endocrinology, The Ninth Hospital of Wuhan City Wuhan 430060, P. R. China.
Juan WeiDepartment of Endocrinology, The Ninth Hospital of Wuhan City Wuhan 430060, P. R. China.
Jianjun HuangDepartment of Endocrinology, The Ninth Hospital of Wuhan City Wuhan 430060, P. R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Some studies were conducted to investigate the association between signal transducer and activator of transcription 4 (STAT4) polymorphisms and diabetes risk. However, the results were inconsistent. We thus did a meta-analysis. We searched the articles in the PubMed, Embase and CNKI databases (the last search updated on November 2014). Pooled odds ratios (OR) with 95% confidence intervals (CI) were derived from random-effects models or fixed-effects models. Ten case-control studies with 18931 cases and 23833 controls were included in this study. STAT4 rs7574865 polymorphism was significantly associated with diabetes risk (OR = 1.28; 95% CI 1.16-1.42; P < 0.00001). This polymorphism also increased type 1 diabetes risk significantly (OR = 1.27; 95% CI 1.15-1.41; P < 0.00001). In the subgroup analysis by ethnicity, a significant association was found among Asians (OR = 1.33; 95% CI 1.04-1.71; P = 0.02) and Caucasians (OR = 1.24; 95% CI 1.12-1.38; P < 0.0001). In the subgroup analysis by age, both children (OR = 1.28; 95% CI 1.12-1.45; P = 0.0002) and adults (OR = 1.27; 95% CI 1.13-1.42; P < 0.0001) with this polymorphism showed increased diabetes risk. Other STAT4 polymorphisms were not investigated in this meta-analysis due to insufficient data. This meta-analysis indicated that STAT4 rs7574865 polymorphism was associated with diabetes risk.

Indexed as

associationDiabetesmeta-analysispolymorphismSTAT4

Identifiers

PMID26064250
PMCPMC4443084

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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 OpenQuestion graph.