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A Pro-Inflammatory Biomarker-Profile Predicts Amputation-Free Survival in Patients with Severe Limb Ischemia

Patients with Severe Limb Ischemia (SLI) have a high risk of amputation and mortality. Here, we investigated a panel of serum biomarkers with the aim of identifying biomarkers for major events and mechanisms that contribute to disease progression in established SLI. A panel of biomarkers including G...

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Autores principales: Gremmels, Hendrik, Teraa, Martin, de Jager, Saskia C. A., Pasterkamp, Gerard, de Borst, Gert J., Verhaar, Marianne C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6656730/
https://www.ncbi.nlm.nih.gov/pubmed/31341203
http://dx.doi.org/10.1038/s41598-019-47217-1
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author Gremmels, Hendrik
Teraa, Martin
de Jager, Saskia C. A.
Pasterkamp, Gerard
de Borst, Gert J.
Verhaar, Marianne C.
author_facet Gremmels, Hendrik
Teraa, Martin
de Jager, Saskia C. A.
Pasterkamp, Gerard
de Borst, Gert J.
Verhaar, Marianne C.
author_sort Gremmels, Hendrik
collection PubMed
description Patients with Severe Limb Ischemia (SLI) have a high risk of amputation and mortality. Here, we investigated a panel of serum biomarkers with the aim of identifying biomarkers for major events and mechanisms that contribute to disease progression in established SLI. A panel of biomarkers including GROα, HGF, SCF, SCGFβ, SDF1α, TRAIL, IL-6, IL-8, FGFβ, GCSF, GMCSF, IP10, MCP1, PDGFbb, RANTES, TNFα, VEGF, sICAM, sVCAM, TM, and E-selectin was measured in serum samples from a subset (n = 108) of the JUVENTAS cohort. The primary outcome was major events, defined as major amputation or death. The inflammatory biomarkers IL-6, IL-8, GROα and IP-10 were significantly elevated in patients who reached a major endpoint. Results were validated in a secondary cohort (n = 146). Cox regression showed that adjusted hazard ratios were 1.40 (95% CI: 1.15–1.70, p = 0.0007) and 1.48 (95% CI 1.16–1.87, p = 0.001) for IL-6 and IP-10 in a fully adjusted model containing both biomarkers. A prediction model using IL-6 and IP-10 showed predictive accuracy with an AUC of ~ 78% in both discovery and validation cohorts, which is higher than previously published models. We conclude that inflammatory biomarkers predict major events in patients with SLI and allow the creation of biomarker-based risk-prediction models.
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spelling pubmed-66567302019-07-29 A Pro-Inflammatory Biomarker-Profile Predicts Amputation-Free Survival in Patients with Severe Limb Ischemia Gremmels, Hendrik Teraa, Martin de Jager, Saskia C. A. Pasterkamp, Gerard de Borst, Gert J. Verhaar, Marianne C. Sci Rep Article Patients with Severe Limb Ischemia (SLI) have a high risk of amputation and mortality. Here, we investigated a panel of serum biomarkers with the aim of identifying biomarkers for major events and mechanisms that contribute to disease progression in established SLI. A panel of biomarkers including GROα, HGF, SCF, SCGFβ, SDF1α, TRAIL, IL-6, IL-8, FGFβ, GCSF, GMCSF, IP10, MCP1, PDGFbb, RANTES, TNFα, VEGF, sICAM, sVCAM, TM, and E-selectin was measured in serum samples from a subset (n = 108) of the JUVENTAS cohort. The primary outcome was major events, defined as major amputation or death. The inflammatory biomarkers IL-6, IL-8, GROα and IP-10 were significantly elevated in patients who reached a major endpoint. Results were validated in a secondary cohort (n = 146). Cox regression showed that adjusted hazard ratios were 1.40 (95% CI: 1.15–1.70, p = 0.0007) and 1.48 (95% CI 1.16–1.87, p = 0.001) for IL-6 and IP-10 in a fully adjusted model containing both biomarkers. A prediction model using IL-6 and IP-10 showed predictive accuracy with an AUC of ~ 78% in both discovery and validation cohorts, which is higher than previously published models. We conclude that inflammatory biomarkers predict major events in patients with SLI and allow the creation of biomarker-based risk-prediction models. Nature Publishing Group UK 2019-07-24 /pmc/articles/PMC6656730/ /pubmed/31341203 http://dx.doi.org/10.1038/s41598-019-47217-1 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Gremmels, Hendrik
Teraa, Martin
de Jager, Saskia C. A.
Pasterkamp, Gerard
de Borst, Gert J.
Verhaar, Marianne C.
A Pro-Inflammatory Biomarker-Profile Predicts Amputation-Free Survival in Patients with Severe Limb Ischemia
title A Pro-Inflammatory Biomarker-Profile Predicts Amputation-Free Survival in Patients with Severe Limb Ischemia
title_full A Pro-Inflammatory Biomarker-Profile Predicts Amputation-Free Survival in Patients with Severe Limb Ischemia
title_fullStr A Pro-Inflammatory Biomarker-Profile Predicts Amputation-Free Survival in Patients with Severe Limb Ischemia
title_full_unstemmed A Pro-Inflammatory Biomarker-Profile Predicts Amputation-Free Survival in Patients with Severe Limb Ischemia
title_short A Pro-Inflammatory Biomarker-Profile Predicts Amputation-Free Survival in Patients with Severe Limb Ischemia
title_sort pro-inflammatory biomarker-profile predicts amputation-free survival in patients with severe limb ischemia
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6656730/
https://www.ncbi.nlm.nih.gov/pubmed/31341203
http://dx.doi.org/10.1038/s41598-019-47217-1
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