Evidence map›Paper›PMID 27788146›Full record

SynthesisPloS one2016

A Systematic Review of Biomarkers and Risk of Incident Type 2 Diabetes: An Overview of Epidemiological, Prediction and Aetiological Research Literature.

Ali Abbasi, Anna-Stina Sahlqvist, Luca Lotta, Julia M Brosnan, Peter Vollenweider, Philippe Giabbanelli, Derek J Nunez, Dawn Waterworth, Robert A Scott, Claudia Langenberg and 1 more

Abstract readSystematic Review
In one paragraph

Synthesis in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 3 pooled it
–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

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

39 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  16. Review
  17. Circulating Nucleic Acid-Based Biomarkers of Type 2 Diabetes.International journal of molecular sciences · 2021
    Review
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  19. Observational
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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

11 authors.

Ali AbbasiMedical Research Council (MRC) Epidemiology Unit, University of Cambridge School of Clinical, Cambridge, United Kingdom.ORCID http://orcid.org/0000-0002-6452-4765
Anna-Stina SahlqvistGlaxoSmithKline, R&D, Stevenage, United Kingdom, RTP NC, King of Prussia, PA, United States of America.
Luca LottaMedical Research Council (MRC) Epidemiology Unit, University of Cambridge School of Clinical, Cambridge, United Kingdom.
Julia M BrosnanPfizer Inc, Cambridge, MA, United States of America.
Peter VollenweiderDepartment of Medicine, Internal Medicine, CHUV, Lausanne, Switzerland.
Philippe GiabbanelliMedical Research Council (MRC) Epidemiology Unit, University of Cambridge School of Clinical, Cambridge, United Kingdom.
Derek J NunezGlaxoSmithKline, R&D, Stevenage, United Kingdom, RTP NC, King of Prussia, PA, United States of America.
Dawn WaterworthGlaxoSmithKline, R&D, Stevenage, United Kingdom, RTP NC, King of Prussia, PA, United States of America.
Robert A ScottMedical Research Council (MRC) Epidemiology Unit, University of Cambridge School of Clinical, Cambridge, United Kingdom.
Claudia LangenbergMedical Research Council (MRC) Epidemiology Unit, University of Cambridge School of Clinical, Cambridge, United Kingdom.
Nicholas J WarehamMedical Research Council (MRC) Epidemiology Unit, University of Cambridge School of Clinical, Cambridge, United Kingdom.

Funding

Medical Research Council MC_UU_12015/1
6 · The paper itself

Abstract

backgroundBlood-based or urinary biomarkers may play a role in quantifying the future risk of type 2 diabetes (T2D) and in understanding possible aetiological pathways to disease. However, no systematic review has been conducted that has identified and provided an overview of available biomarkers for incident T2D. We aimed to systematically review the associations of biomarkers with risk of developing T2D and to highlight evidence gaps in the existing literature regarding the predictive and aetiological value of these biomarkers and to direct future research in this field. METHODS AND

findingsWe systematically searched PubMed MEDLINE (January 2000 until March 2015) and Embase (until January 2016) databases for observational studies of biomarkers and incident T2D according to the 2009 PRISMA guidelines. We also searched availability of meta-analyses, Mendelian randomisation and prediction research for the identified biomarkers. We reviewed 3910 titles (705 abstracts) and 164 full papers and included 139 papers from 69 cohort studies that described the prospective relationships between 167 blood-based or urinary biomarkers and incident T2D. Only 35 biomarkers were reported in large scale studies with more than 1000 T2D cases, and thus the evidence for association was inconclusive for the majority of biomarkers. Fourteen biomarkers have been investigated using Mendelian randomisation approaches. Only for one biomarker was there strong observational evidence of association and evidence from genetic association studies that was compatible with an underlying causal association. In additional search for T2D prediction, we found only half of biomarkers were examined with formal evidence of predictive value for a minority of these biomarkers. Most biomarkers did not enhance the strength of prediction, but the strongest evidence for prediction was for biomarkers that quantify measures of glycaemia.

conclusionsThis study presents an extensive review of the current state of the literature to inform the strategy for future interrogation of existing and newly described biomarkers for T2D. Many biomarkers have been reported to be associated with the risk of developing T2D. The evidence of their value in adding to understanding of causal pathways to disease is very limited so far. The utility of most biomarkers remains largely unknown in clinical prediction. Future research should focus on providing good genetic instruments across consortia for possible biomarkers in Mendelian randomisation, prioritising biomarkers for measurement in large-scale cohort studies and examining predictive utility of biomarkers for a given context.

Indexed as

BiomarkersDiabetes Mellitus, Type 2HumansPredictive Value of TestsRiskBiomarkers

Identifiers

PMID27788146
PMCPMC5082867

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.