Abstract
Objectives
Pain relief and joint space narrowing prevention are the clinically accepted evidence of effective osteoarthritis [OA] treatment. However, previous studies show no clear correlation between them. In this 21-month non-treatment study, we investigated relationships between alternative OA biomarkers and knee pain.
Methods
One hundred fifty-nine subjects were recruited, including healthy volunteers with known knee problems. Two biochemical degradation markers were measured; a serum bone marker [sCTX-I] and a urinary cartilage marker [uCTX-II]. Seven magnetic resonance imaging biomarkers were measured, assessing cartilage volume, thickness, curvature, smoothness, and homogeneity. Joint space width was measured from radiographs. All imaging markers were measured in the medial tibio-femoral compartments.
The knee pain during the previous 24 hours was scored by a visual analog scale. Biomarkers were measured at baseline and follow-up, except for pain that was only scored at follow-up. The relationships to pain presence and severity were evaluated cross-sectionally at follow-up and longitudinally to biomarker changes from baseline to follow-up.
Results
The analysis included 134 subjects with baseline age 56 ± 16, body mass index [BMI] 26 ± 4, and 53 percent without radiographic OA. After normalization for gender, age, and BMI, the strongest cross-sectional relationship to pain presence was uCTX-II [receiver-operators characteristics area], area under the curve [AUC] 0.65, P < 0.01; odds ratio [OR] 3.6, P < 0.01. The strongest longitudinal relationships were to uCTX-II [AUC 0.62, P < 0.05, OR 3.5, P < 0.01] and cartilage homogeneity [AUC 0.65, P < 0.01, OR 3.0, P < 0.01].
Conclusions
Unlike imaging markers of cartilage quantity, cartilage degradation estimated by uCTX-II was related to the presence of pain. This observation may aid the understanding of OA-related pain.
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ACKNOWLEDGEMENT
We gratefully acknowledge the partial funding from the Danish Research Foundation [Den Danske Forskningsfond] supporting this work. We also gratefully acknowledge the partial funding from Synarc.