Research article

Identification of progressors in osteoarthritis by combining biochemical and MRI-based markers

Erik B Dam¹ , Marco Loog^1,2,3 , Claus Christiansen¹ , Inger Byrjalsen¹ , Jenny Folkesson² , Mads Nielsen^1,2 , Arish A Qazi² , Paola C Pettersen⁴ , Patrick Garnero⁵ and Morten A Karsdal¹

¹  Nordic Bioscience, Herlev Hovedgade 207, 2730 Herlev, Denmark

²  University of Copenhagen, Department of Computer Science, Universitetsparken 1, 2100 Copenhagen, Denmark

³  Delft University of Technology, Faculty of Electrical Engineering, Mathematics, and Computer Science, Mekelweg 4, 2628 CD Delft, The Netherlands

⁴  Center for Clinical and Basic Research, Ballerup Byvej 222, 2750 Ballerup, Denmark

⁵  CCBR-Synarc, Molecular Markers, Rue Montbrillant 16, 69003 Lyon, France

author email corresponding author email

Arthritis Research & Therapy 2009, 11:R115doi:10.1186/ar2774

Published:	24 July 2009

See related editorial by Williams, http://arthritis-research.com/content/11/5/130

Abstract

Introduction

At present, no disease-modifying osteoarthritis drugs (DMOADS) are approved by the FDA (US Food and Drug Administration); possibly partly due to inadequate trial design since efficacy demonstration requires disease progression in the placebo group. We investigated whether combinations of biochemical and magnetic resonance imaging (MRI)-based markers provided effective diagnostic and prognostic tools for identifying subjects with high risk of progression. Specifically, we investigated aggregate cartilage longevity markers combining markers of breakdown, quantity, and quality.

Methods

The study included healthy individuals and subjects with radiographic osteoarthritis. In total, 159 subjects (48% female, age 56.0 ± 15.9 years, body mass index 26.1 ± 4.2 kg/m²) were recruited. At baseline and after 21 months, biochemical (urinary collagen type II C-telopeptide fragment, CTX-II) and MRI-based markers were quantified. MRI markers included cartilage volume, thickness, area, roughness, homogeneity, and curvature in the medial tibio-femoral compartment. Joint space width was measured from radiographs and at 21 months to assess progression of joint damage.

Results

Cartilage roughness had the highest diagnostic accuracy quantified as the area under the receiver-operator characteristics curve (AUC) of 0.80 (95% confidence interval: 0.69 to 0.91) among the individual markers (higher than all others, P < 0.05) to distinguish subjects with radiographic osteoarthritis from healthy controls. Diagnostically, cartilage longevity scored AUC 0.84 (0.77 to 0.92, higher than roughness: P = 0.03). For prediction of longitudinal radiographic progression based on baseline marker values, the individual prognostic marker with highest AUC was homogeneity at 0.71 (0.56 to 0.81). Prognostically, cartilage longevity scored AUC 0.77 (0.62 to 0.90, borderline higher than homogeneity: P = 0.12). When comparing patients in the highest quartile for the longevity score to lowest quartile, the odds ratio of progression was 20.0 (95% confidence interval: 6.4 to 62.1).

Conclusions

Combination of biochemical and MRI-based biomarkers improved diagnosis and prognosis of knee osteoarthritis and may be useful to select high-risk patients for inclusion in DMOAD clinical trials.