Evidence map›Paper›PMID 28777936›Full record

ArticleAtherosclerosis2017

Comparison of non-traditional biomarkers, and combinations of biomarkers, for vascular risk prediction in people with type 2 diabetes: The Edinburgh Type 2 Diabetes Study.

Anna H Price, Christopher J Weir, Paul Welsh, Stela McLachlan, Mark W J Strachan, Naveed Sattar, Jackie F Price

Registry-linked trialOpen access · hybridAbstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Atherosclerosis, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04388280 (Functional and Anatomic Imaging Versus No Testing in Asymptomatic High-risk Diabetic Patients), which is not on this map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 2 pooled it
2.0field-weighted citation impact, top 14% 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.

NCT04388280 naunknown statusnot on this mapstarted 2021, after this paper: background citation

Functional and Anatomic Imaging Versus No Testing in Asymptomatic High-risk Diabetic Patients

TypeinterventionalSponsorClinical Centre of SerbiaRan2021 to 2023Enrolled400ConditionsAsymptomatic, High Risk, DiabetesArmsEchocardiography, CT angiography
3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 2 syntheses or guidelines pooled it, 20 citations in OpenAlex.

  1. Pooled it
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  3. Article
  4. Review
  5. Article
  6. Article
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  8. 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

7 authors at 3 institutions in 1 country.

Anna H PriceUsher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, Scotland, UK. Electronic address: A.H.Price@ed.ac.uk.
Christopher J WeirUsher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, Scotland, UK; Edinburgh Clinical Trials Unit, University of Edinburgh, Scotland, UK.
Paul WelshGlasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, Scotland, UK.
Stela McLachlanUsher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, Scotland, UK.
Mark W J StrachanMetabolic Unit, Western General Hospital, Edinburgh, Scotland, UK.
Naveed SattarGlasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, Scotland, UK.
Jackie F PriceUsher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, Scotland, UK. Electronic address: Jackie.Price@ed.ac.uk.
University of Edinburgh · GBUniversity of Glasgow · GBWestern General Hospital · GB

Funding

Medical Research Council G0500877Medical Research Council MR/N005813/1
6 · The paper itself

Abstract

BACKGROUND AND

aimsWe aimed at comparing the impact of multiple non-traditional biomarkers (ankle brachial pressure index (ABI), N-terminal pro-brain natriuretic peptide (NT-proBNP), high sensitivity cardiac troponin (hs-cTnT), gamma-glutamyl transpeptidase (GGT) and four markers of systemic inflammation), both individually and in combination, on cardiovascular risk prediction, over and above traditional risk factors incorporated in the QRISK2 score, in older people with type 2 diabetes.

methodsWe conducted a prospective study of 1066 men and women aged 60-75 years with type 2 diabetes mellitus, living in Lothian, Scotland.

resultsAfter 8 years, 205 cardiovascular events occurred. Higher levels of hs-cTNT and NT-proBNP and lower ABI at baseline were associated with increased risk of CV events, independently of traditional risk factors (basic model). The C statistic of 0.722 (95% CI 0.681, 0.763) for the basic model increased on addition of individual biomarkers, most markedly for hs-cTnT (0.732; 0.690, 0.774)). Models including different combinations of biomarkers had even greater C statistics, with the highest for ABI, hs-cTnT and GGT combined (0.740; 0.699, 0.781).

conclusionsIndividually, hs-cTnT appeared to be the most promising biomarker in terms of improving vascular risk prediction in people with type 2 diabetes, over and above traditional risk factors incorporated in the QRISK2 score. Combining several non-traditional biomarkers added further predictive value, and this approach merits further investigation when developing cost effective risk prediction tools for use in clinical practice.

Indexed as

AgedAnkle Brachial IndexBiomarkersCardiovascular DiseasesDiabetes Mellitus, Type 2Femalegamma-GlutamyltransferaseHumansIncidenceInflammation MediatorsLongitudinal StudiesMaleMiddle AgedNatriuretic Peptide, BrainPeptide FragmentsPredictive Value of TestsBiomarkersgamma-Glutamyltransferasegamma-glutamyltransferase, humanInflammation MediatorsNatriuretic Peptide, BrainPeptide Fragmentspro-brain natriuretic peptide (1-76)Troponin TBiomarkersCardiovascular diseaseEpidemiologyRisk predictionType 2 diabetes

Identifiers

PMID28777936
PMCPMC5603967
OpenAlexW2735408048

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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.