Biomarkers of Vascular Inflammation for Cardiovascular Risk Prognostication: A Meta-Analysis.


Journal

JACC. Cardiovascular imaging
ISSN: 1876-7591
Titre abrégé: JACC Cardiovasc Imaging
Pays: United States
ID NLM: 101467978

Informations de publication

Date de publication:
03 2022
Historique:
received: 12 08 2021
revised: 08 09 2021
accepted: 10 09 2021
pubmed: 22 11 2021
medline: 28 4 2022
entrez: 21 11 2021
Statut: ppublish

Résumé

The purpose of this study was to systematically explore the added value of biomarkers of vascular inflammation for cardiovascular prognostication on top of clinical risk factors. Measurement of biomarkers of vascular inflammation is advocated for the risk stratification for coronary heart disease (CHD). We systematically explored published reports in MEDLINE for cohort studies on the prognostic value of common biomarkers of vascular inflammation in stable patients without known CHD. These included common circulating inflammatory biomarkers (ie, C-reactive protein, interleukin-6 and tumor necrosis factor-a, arterial positron emission tomography/computed tomography and coronary computed tomography angiography-derived biomarkers of vascular inflammation, including anatomical high-risk plaque features and perivascular fat imaging. The main endpoint was the difference in c-index (Δ[c-index]) with the use of inflammatory biomarkers for major adverse cardiovascular events (MACEs) and mortality. We calculated I A total of 104,826 relevant studies were screened and a final of 39 independent studies (175,778 individuals) were included in the quantitative synthesis. Biomarkers of vascular inflammation provided added prognostic value for the composite endpoint and for MACEs only (pooled estimate for Δ[c-index]% 2.9, 95% CI: 1.7-4.1 and 3.1, 95% CI: 1.8-4.5, respectively). Coronary computed tomography angiography-related biomarkers were associated with the highest added prognostic value for MACEs: high-risk plaques 5.8%, 95% CI: 0.6 to 11.0, and perivascular adipose tissue (on top of coronary atherosclerosis extent and high-risk plaques): 8.2%, 95% CI: 4.0 to 12.5). In meta-regression analysis, the prognostic value of inflammatory biomarkers was independent of other confounders including study size, length of follow-up, population event incidence, the performance of the baseline model, and the level of statistical adjustment. Limitations in the published literature include the lack of reporting of other metrics of improvement of risk stratification, the net clinical benefit, or the cost-effectiveness of such biomarkers in clinical practice. The use of biomarkers of vascular inflammation enhances risk discrimination for cardiovascular events.

Sections du résumé

OBJECTIVES
The purpose of this study was to systematically explore the added value of biomarkers of vascular inflammation for cardiovascular prognostication on top of clinical risk factors.
BACKGROUND
Measurement of biomarkers of vascular inflammation is advocated for the risk stratification for coronary heart disease (CHD).
METHODS
We systematically explored published reports in MEDLINE for cohort studies on the prognostic value of common biomarkers of vascular inflammation in stable patients without known CHD. These included common circulating inflammatory biomarkers (ie, C-reactive protein, interleukin-6 and tumor necrosis factor-a, arterial positron emission tomography/computed tomography and coronary computed tomography angiography-derived biomarkers of vascular inflammation, including anatomical high-risk plaque features and perivascular fat imaging. The main endpoint was the difference in c-index (Δ[c-index]) with the use of inflammatory biomarkers for major adverse cardiovascular events (MACEs) and mortality. We calculated I
RESULTS
A total of 104,826 relevant studies were screened and a final of 39 independent studies (175,778 individuals) were included in the quantitative synthesis. Biomarkers of vascular inflammation provided added prognostic value for the composite endpoint and for MACEs only (pooled estimate for Δ[c-index]% 2.9, 95% CI: 1.7-4.1 and 3.1, 95% CI: 1.8-4.5, respectively). Coronary computed tomography angiography-related biomarkers were associated with the highest added prognostic value for MACEs: high-risk plaques 5.8%, 95% CI: 0.6 to 11.0, and perivascular adipose tissue (on top of coronary atherosclerosis extent and high-risk plaques): 8.2%, 95% CI: 4.0 to 12.5). In meta-regression analysis, the prognostic value of inflammatory biomarkers was independent of other confounders including study size, length of follow-up, population event incidence, the performance of the baseline model, and the level of statistical adjustment. Limitations in the published literature include the lack of reporting of other metrics of improvement of risk stratification, the net clinical benefit, or the cost-effectiveness of such biomarkers in clinical practice.
CONCLUSIONS
The use of biomarkers of vascular inflammation enhances risk discrimination for cardiovascular events.

Identifiants

pubmed: 34801448
pii: S1936-878X(21)00698-7
doi: 10.1016/j.jcmg.2021.09.014
pii:
doi:

Substances chimiques

Biomarkers 0

Types de publication

Journal Article Meta-Analysis

Langues

eng

Sous-ensembles de citation

IM

Pagination

460-471

Subventions

Organisme : British Heart Foundation
ID : CH/F/21/90009
Pays : United Kingdom
Organisme : British Heart Foundation
ID : FS/16/15/32047
Pays : United Kingdom
Organisme : British Heart Foundation
ID : TG/16/3/32687
Pays : United Kingdom

Commentaires et corrections

Type : CommentIn

Informations de copyright

Copyright © 2022 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Funding Support and Author Disclosures Dr Antoniades is a founder and shareholder of Caristo Diagnostics Ltd, a company that specialized in computed tomography imaging diagnostics. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.

Auteurs

Alexios S Antonopoulos (AS)

1(st) Cardiology Department, School of Health Sciences, National and Kapodistrian University of Athens, Greece; RDM Division of Cardiovascular Medicine, University of Oxford, United Kingdom. Electronic address: alexios.antonopoulos@cardiov.ox.ac.uk.

Andreas Angelopoulos (A)

1(st) Cardiology Department, School of Health Sciences, National and Kapodistrian University of Athens, Greece.

Paraskevi Papanikolaou (P)

1(st) Cardiology Department, School of Health Sciences, National and Kapodistrian University of Athens, Greece.

Spyridon Simantiris (S)

1(st) Cardiology Department, School of Health Sciences, National and Kapodistrian University of Athens, Greece.

Evangelos K Oikonomou (EK)

RDM Division of Cardiovascular Medicine, University of Oxford, United Kingdom; Department of Internal Medicine, Yale School of Medicine, Yale-New Haven Hospital, Connecticut, USA.

Konstantinos Vamvakaris (K)

1(st) Cardiology Department, School of Health Sciences, National and Kapodistrian University of Athens, Greece.

Alkmini Koumpoura (A)

1(st) Cardiology Department, School of Health Sciences, National and Kapodistrian University of Athens, Greece.

Maria Farmaki (M)

1(st) Cardiology Department, School of Health Sciences, National and Kapodistrian University of Athens, Greece.

Marialena Trivella (M)

Centre for Statistics in Medicine, University of Oxford, United Kingdom.

Charalambos Vlachopoulos (C)

1(st) Cardiology Department, School of Health Sciences, National and Kapodistrian University of Athens, Greece.

Konstantinos Tsioufis (K)

1(st) Cardiology Department, School of Health Sciences, National and Kapodistrian University of Athens, Greece.

Charalambos Antoniades (C)

RDM Division of Cardiovascular Medicine, University of Oxford, United Kingdom.

Dimitris Tousoulis (D)

1(st) Cardiology Department, School of Health Sciences, National and Kapodistrian University of Athens, Greece.

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