Detection of progression of radiographic joint damage in case of very early osteoarthritis: Sensitivity to change of quantitative analysis compared to qualitative grading

Kinds, M.B., Marijnissen, A.C.A, Bierma-Zeinstra, S.M.A., Bijlsma, J.W.J., Vincken, K.L., Viergever, M.A., Lafeber, F.P.J.G., Welsing, P.M.J.


Rheumatology Reports [E] 4 (1), p. 27-33


For more tailored treatment of osteoarthritis it is worthy to identify different subpopulations early in the disease. Objective of this study is to evaluate whether the sensitivity to detect progression of radiographic features, which may add to this identification, can be improved by quantitative measurement (using Knee Images Digital Analysis; KIDA), compared to qualitative grading (according to the Altman atlas). Among individuals with early signs related to osteoarthritis (Cohort Hip and Cohort Knee, Check) symptomatic knees (n=1082) were selected. Standardized baseline and two-year follow-up radiographs were evaluated for joint space narrowing, osteophyte formation, and bone density changes using KIDA measurement and Altman scales. Sensitivity to change was determined by calculating the standardized response mean (SRM). For all distinct KIDA parameters, the smallest detectable difference was calculated to define radiographic changes at the individual level. The percentage of knees that changed was compared between KIDA measurement and Altman grading. Also agreement between both methods was evaluated. Studying radiographic progression in knees with early signs related to osteoarthritis showed, for all KIDA and Altman parameters, a small SRM and radiographic change in a small percentage of knees. The sensitivity to detect radiographic progression was similar for KIDA measurement and Altman grading. However, agreement between the Altman and KIDA method was limited (kappa ≤0.20). Although sensitivity to change is limited, similar for KIDA measurement and Altman grading, this may not exclude that measurement of separate features might be useful to distinguish subpopulations of osteoarthritis later in the disease. © M.B. Kinds et al., 2012.