Evidence mapPaperPMID 24008910Full record

SynthesisAmerican journal of epidemiology2013

Predicting risk of type 2 diabetes mellitus with genetic risk models on the basis of established genome-wide association markers: a systematic review.

Wei Bao, Frank B Hu, Shuang Rong, Ying Rong, Katherine Bowers, Enrique F Schisterman, Liegang Liu, Cuilin Zhang

Open access · bronzeAbstract readEvaluation StudySystematic Review
In one paragraph

Synthesis in American journal of epidemiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
8.8field-weighted citation impact, top 2% 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

30 citing papers in PubMed, 66 citations in OpenAlex.

  1. Trial
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  8. Observational
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  13. Glucose tolerance female-specific QTL mapped in collaborative cross mice.Mammalian genome : official journal of the International Mammalian Genome Society · 2017
    Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. A Review of Emerging Technologies for the Management of Diabetes Mellitus.IEEE transactions on bio-medical engineering · 2015
    Review
  19. Article
  20. 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

8 authors.

Wei Bao
Frank B Hu
Shuang Rong
Ying Rong
Katherine Bowers
Enrique F Schisterman
Liegang Liu
Cuilin Zhang

Funding

BIOCHEMICAL AND GENETIC MARKERS OF TYPE 2 DIABETES RISKR01DK058845 · BRIGHAM AND WOMEN'S HOSPITAL · 2001 to 2005
$3.0M
Intramural NIH HHS ZIA HD008916NIDDK NIH HHS DK58845NIDDK NIH HHS R01 DK058845
6 · The paper itself

Abstract

This study aimed to evaluate the predictive performance of genetic risk models based on risk loci identified and/or confirmed in genome-wide association studies for type 2 diabetes mellitus. A systematic literature search was conducted in the PubMed/MEDLINE and EMBASE databases through April 13, 2012, and published data relevant to the prediction of type 2 diabetes based on genome-wide association marker-based risk models (GRMs) were included. Of the 1,234 potentially relevant articles, 21 articles representing 23 studies were eligible for inclusion. The median area under the receiver operating characteristic curve (AUC) among eligible studies was 0.60 (range, 0.55-0.68), which did not differ appreciably by study design, sample size, participants' race/ethnicity, or the number of genetic markers included in the GRMs. In addition, the AUCs for type 2 diabetes did not improve appreciably with the addition of genetic markers into conventional risk factor-based models (median AUC, 0.79 (range, 0.63-0.91) vs. median AUC, 0.78 (range, 0.63-0.90), respectively). A limited number of included studies used reclassification measures and yielded inconsistent results. In conclusion, GRMs showed a low predictive performance for risk of type 2 diabetes, irrespective of study design, participants' race/ethnicity, and the number of genetic markers included. Moreover, the addition of genome-wide association markers into conventional risk models produced little improvement in predictive performance.

Indexed as

Genetic Predisposition to DiseaseModels, GeneticArea Under CurveDiabetes Mellitus, Type 2Genome-Wide Association StudyHumansPredictive Value of TestsRiskarea under the curvereceiver operating characteristic curvesingle nucleotide polymorphismtype 2 diabetes mellitus

Identifiers

PMID24008910
PMCPMC3792732
OpenAlexW2170801801

What Socratic 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 Socratic graph.