Added value of biomarkers compared with clinical parameters for the prediction of radiographic spinal progression in axial spondyloarthritis.


Journal

Rheumatology (Oxford, England)
ISSN: 1462-0332
Titre abrégé: Rheumatology (Oxford)
Pays: England
ID NLM: 100883501

Informations de publication

Date de publication:
01 09 2019
Historique:
received: 12 04 2018
revised: 26 12 2018
pubmed: 5 3 2019
medline: 21 3 2020
entrez: 5 3 2019
Statut: ppublish

Résumé

The objective of this study was to examine whether adding biomarkers to routine clinical parameters improves prediction of radiographic spinal progression in axial spondyloarthritis. One hundred and seventeen patients with ankylosing spondylitis who completed the Effects of NSAIDs on RAdiographic Damage in Ankylosing Spondylitis (ENRADAS) trial were included. Radiographic spinal progression was defined as worsening of the modified Stoke Ankylosing Spondylitis Spine Score by ⩾2 points after 2 years. A clinical prediction model was constructed out of baseline syndesmophytes, elevated CRP, cigarette smoking and male sex. The following serum biomarkers were measured at baseline by ELISA: MMP3, VEGF, calprotectin, leptin, high molecular weight adiponectin, osteoprotegerin, sclerostin, N-terminal telopeptide, procollagen type II N-terminal propeptide and serum amyloid A. Repeated cross-validation analyses revealed one biomarker combination with potential added predictive value in addition to the clinical model: leptin + high molecular weight adiponectin + VEGF. This biomarker combination showed an area under the curve (AUC)Biomarkers = 0.731 (95% CI: 0.614, 0.848), which was numerically superior to the clinical model [AUCClinical = 0.665 (95% CI: 0.553, 0.776)]. A combination of clinical parameters + biomarkers showed an improved predictive value compared with the clinical model reflected by AUCClinical+Biomarkers = 0.768 (95% CI: 0.666, 0.871), though not statistically significant (P = 0.051). However, by considering the part of the receiver operating characteristic curve with a specificity ⩾75% resulting in partial AUC (pAUC), the improvement becomes significant (pAUCClinical+Biomarkers = 0.119; pAUCClinical = 0.053; P = 0.01). Biomarkers show potential to improve the prediction of radiographic spinal progression in axial spondyloarthritis when used in addition to the clinical parameters, though the added value seems to be rather small.

Identifiants

pubmed: 30830164
pii: 5369188
doi: 10.1093/rheumatology/kez025
doi:

Substances chimiques

Anti-Inflammatory Agents, Non-Steroidal 0
Biomarkers 0
Inflammation Mediators 0
LEP protein, human 0
Leptin 0
VEGFA protein, human 0
Vascular Endothelial Growth Factor A 0

Types de publication

Journal Article Randomized Controlled Trial Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1556-1564

Commentaires et corrections

Type : CommentIn

Informations de copyright

© The Author(s) 2019. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Auteurs

Judith Rademacher (J)

Department of Gastroenterology, Infectiology and Rheumatology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin.
Berlin Institute of Health, Berlin.

Lorraine Madeline Tietz (LM)

Department of Gastroenterology, Infectiology and Rheumatology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin.
Berlin Institute of Health, Berlin.

Lien Le (L)

Institute of Medical Informatics, Biometry, and Epidemiology, Ludwig-Maximilian University, Munich.

Agnes Hartl (A)

Department of Gastroenterology, Infectiology and Rheumatology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin.
Berlin Institute of Health, Berlin.

Kay-Geert A Hermann (KA)

Berlin Institute of Health, Berlin.
Department of Radiology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin.

Joachim Sieper (J)

Department of Gastroenterology, Infectiology and Rheumatology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin.
Berlin Institute of Health, Berlin.

Ulrich Mansmann (U)

Institute of Medical Informatics, Biometry, and Epidemiology, Ludwig-Maximilian University, Munich.

Martin Rudwaleit (M)

Department of Gastroenterology, Infectiology and Rheumatology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin.
Berlin Institute of Health, Berlin.
Department of Internal Medicine and Rheumatology, Klinikum Bielefeld Rosenhöhe, Bielefeld.

Denis Poddubnyy (D)

Department of Gastroenterology, Infectiology and Rheumatology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin.
Berlin Institute of Health, Berlin.
Department of Epidemiology, German Rheumatism Research Centre, Berlin, Germany.

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Classifications MeSH