Evidence map›Paper›PMID 30185661›Full record

ArticleJCI insight2018

Large-scale plasma lipidomic profiling identifies lipids that predict cardiovascular events in secondary prevention.

Piyushkumar A Mundra, Christopher K Barlow, Paul J Nestel, Elizabeth H Barnes, Adrienne Kirby, Peter Thompson, David R Sullivan, Zahir H Alshehry, Natalie A Mellett, Kevin Huynh and 13 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in JCI insight, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 92 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
92citing papers in PubMed, 2 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

92 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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32 more citing papers are in PubMed but not listed here.

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

23 authors.

Piyushkumar A MundraBaker Heart and Diabetes Institute, Melbourne, Victoria, Australia.
Christopher K BarlowBaker Heart and Diabetes Institute, Melbourne, Victoria, Australia.
Paul J NestelBaker Heart and Diabetes Institute, Melbourne, Victoria, Australia.
Elizabeth H BarnesNational Health and Medical Research Council Clinical Trials Centre, University of Sydney, Sydney, New South Wales, Australia.
Adrienne KirbyNational Health and Medical Research Council Clinical Trials Centre, University of Sydney, Sydney, New South Wales, Australia.
Peter ThompsonSir Charles Gairdner Hospital, Perth, Western Australia, Australia.
David R SullivanRoyal Prince Alfred Hospital, Sydney, New South Wales, Australia.
Zahir H AlshehryBaker Heart and Diabetes Institute, Melbourne, Victoria, Australia.
Natalie A MellettBaker Heart and Diabetes Institute, Melbourne, Victoria, Australia.
Kevin HuynhBaker Heart and Diabetes Institute, Melbourne, Victoria, Australia.
Kaushala S JayawardanaBaker Heart and Diabetes Institute, Melbourne, Victoria, Australia.
Corey GilesBaker Heart and Diabetes Institute, Melbourne, Victoria, Australia.
Malcolm J McConvilleDepartment of Biochemistry and Molecular Biology, University of Melbourne, Parkville, Victoria, Australia.
Sophia ZoungasThe George Institute for Global Health, Sydney, New South Wales, Australia.
Graham S HillisThe George Institute for Global Health, Sydney, New South Wales, Australia.
John ChalmersThe George Institute for Global Health, Sydney, New South Wales, Australia.
Mark WoodwardThe George Institute for Global Health, Sydney, New South Wales, Australia.
Gerard WongBaker Heart and Diabetes Institute, Melbourne, Victoria, Australia.
Bronwyn A KingwellBaker Heart and Diabetes Institute, Melbourne, Victoria, Australia.
John SimesNational Health and Medical Research Council Clinical Trials Centre, University of Sydney, Sydney, New South Wales, Australia.
Andrew M TonkinMonash University, Melbourne, Victoria, Australia.
Peter J MeikleBaker Heart and Diabetes Institute, Melbourne, Victoria, Australia.
LIPID Study Investigators

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPlasma lipidomic measures may enable improved prediction of cardiovascular outcomes in secondary prevention. The aim of this study is to determine the association of plasma lipidomic measurements with cardiovascular events and assess their potential to predict such events.

methodsPlasma lipids (n = 342) were measured in a retrospective subcohort (n = 5,991) of the LIPID study. Proportional hazards regression was used to identify lipids associated with future cardiovascular events (nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death) and cardiovascular death. Multivariable models adding lipid species to traditional risk factors were created using lipid ranking established from the Akaike information criterion within a 5-fold cross-validation framework. The results were tested on a diabetic case cohort from the ADVANCE study (n = 3,779).

resultsSpecific ceramide species, sphingolipids, phospholipids, and neutral lipids containing omega-6 fatty acids or odd-chain fatty acids were associated with future cardiovascular events (106 species) and cardiovascular death (139 species). The addition of 7 lipid species to a base model (11 conventional risk factors) resulted in an increase in the C-statistics from 0.629 (95% CI, 0.628-0.630) to 0.654 (95% CI, 0.653-0.656) for prediction of cardiovascular events and from 0.673 (95% CI, 0.671-0.675) to 0.727 (95% CI, 0.725-0.728) for prediction of cardiovascular death. Categorical net reclassification improvements for cardiovascular events and cardiovascular death were 0.083 (95% CI, 0.081-0.086) and 0.166 (95% CI, 0.162-0.170), respectively. Evaluation on the ADVANCE case cohort demonstrated significant improvement on the base models.

conclusionsThe improvement in the prediction of cardiovascular outcomes, above conventional risk factors, demonstrates the potential of plasma lipidomic profiles as biomarkers for cardiovascular risk stratification in secondary prevention.

fundingBristol-Myers Squibb, the National Health and Medical Research Council of Australia (grants 211086, 358395, and 1029754), and the Operational Infrastructure Support Program of the Victorian government of Australia.

Indexed as

Lipid MetabolismSecondary PreventionAgedBiomarkersCardiovascular DiseasesCardiovascular SystemFemaleHumansLipidsMaleMiddle AgedMultivariate AnalysisMyocardial InfarctionRetrospective StudiesRisk FactorsBiomarkersLipidsAtherosclerosisCardiologyCardiovascular diseaseMetabolism

Identifiers

PMID30185661
PMCPMC6171797

What OpenQuestion holds

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Registered trials

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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.