Objective: To determine the within- and between-patient variability in the concentrations of synovial fluid, serum and urine markers of joint tissue metabolism in a cohort of patients with knee pain and cartilage changes consistent with early-stage knee osteoarthritis.
Design: Samples of synovial fluid, serum, and urine were obtained from 52 patients on eight different occasions during 1 year, as part of a clinical trial in patients with cartilage abnormalities and knee pain. In joint fluid, aggrecan fragments were quantified by dye precipitation and enzyme-linked immunosorbent assay (ELISA), and matrix metalloproteinases-1 and -3, and tissue inhibitor of metalloproteinases-1 by sandwich ELISAs. In serum, keratan sulfate was quantified by ELISA. Type I collagen N-telopeptide cross-links in urine were determined by ELISA.
Results: The degree of cross-sectional variability in marker concentrations did not vary between the different sampling occasions, and did not differ between the periods of weeks 0 (baseline), 1-4 (treatment) and 13-26 (follow-up). Both between-patient and within-patient coefficients of variation varied for markers in different body fluid compartments, with the lowest variability for serum keratan sulfate, followed by urine type I collagen N-telopeptide crosslinks, and the highest for synovial fluid markers. For synovial fluid, aggrecan fragments showed the least variability, and matrix metalloproteinases the highest. One patient with septic arthritis showed a fivefold peak increase in joint fluid aggrecan fragment concentrations, while the concentration of matrix metalloproteinase-3 increased 100-fold.
Conclusions: Molecular markers of joint tissue metabolism have been suggested as, for example, outcome measures for clinical trials of disease-modifying drugs in osteoarthritis. This report is the first to present data on between- and within-patient variability for such molecular markers in three different body fluid compartments in stable cohort of patients. The availability of such data enables calculations to determine the number of patients needed in prospective studies using these markers as outcome measures.