Evaluation of separate quantitative radiographic features adds to the prediction of incident radiographic osteoarthritis in individuals with recent onset of knee pain: 5-year follow-up in the CHECK cohort

Objective: Detailed radiographic evaluation might enable the identification of osteoarthritis (OA) earlier in the disease. This study evaluated whether and which separate quantitative features on knee radiographs of individuals with recent onset knee pain are associated with incidence of radiographic OA and persistence and/or progression of clinical OA during 5-year follow-up.

Method: From the Cohort Hip & Cohort Knee study participants with knee pain at baseline were evaluated. Radiographic OA development was defined as Kellgren & Lawrence (K&L) grade ≥ II at 5-year follow-up. Clinical OA was defined as persistent knee pain and as progression of Westen Ontario & McMaster Universities Osteoarthritis index (WOMAC) pain and function score during follow-up. At baseline radiographic damage was determined by quantitative measurement of separate features using Knee Images Digital Analysis, and by K&L-grading.

Results: Measuring osteophyte area [odds ratio (OR) =7.0] and minimum joint space width (OR=0.7), in addition to demographic and clinical characteristics, improved the prediction of radiographic OA 5 years later [area under curve receiver operating characteristic=0.74 vs 0.64 without radiographic features]. When the predictive score (based on multivariate regression coefficients) was larger than the cut-off for optimal specificity, the chance of incident radiographic OA was 54% instead of the prior probability of 19%. Evaluating separate quantitative features performed slightly better than K&L-grading (AUC=0.70). Radiographic characteristics hardly added to prediction of clinical OA.

Conclusion: In individuals with onset knee pain, radiographic characteristics added to the prediction of radiographic OA development 5 years later. Quantitative radiographic evaluation in individuals with suspected OA is worthwhile when determining treatment strategies and designing clinical trials.