Abstract
OBJECTIVES The objective of this study was to examine whether adding biomarkers to routine clinical parameters improves prediction of radiographic spinal progression in axial spondyloarthritis. METHODS 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. RESULTS 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). CONCLUSION 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.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Medizin > Institut für Medizinische Informationsverarbeitung, Biometrie und Epidemiologie |
Themengebiete: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit |
ISSN: | 1462-0324 |
Sprache: | Englisch |
Dokumenten ID: | 61809 |
Datum der Veröffentlichung auf Open Access LMU: | 09. Mai 2019, 08:31 |
Letzte Änderungen: | 04. Nov. 2020, 13:39 |