The Prognostic Potential of End-Stage Knee Osteoarthritis and Its Components to Predict Knee Replacement: Data From the Osteoarthritis Initiative.

OBJECTIVE:We aimed to determine how 2 definitions of end-stage knee osteoarthritis (esKOA) and each component (knee symptoms, persistent knee pain, radiographic severity, and presence of limited mobility or instability) related to future knee replacement (KR). METHODS:We performed knee-based analyses of Osteoarthritis Initiative data from baseline to the first 4 annual follow-up visits, and data on KR from baseline until the fifth yearly contact. We calculated a base model using common risk factors for KR in logistic regression models with generalized estimating equations. We assessed model performance with area under the receiver-operating characteristic curve (AUC) and Hosmer-Lemeshow test. We then added esKOA or each component from the visit (< 12 months) before a KR and change in the year before a KR. We calculated the net reclassification improvement (NRI) index and the integrated discrimination improvement (IDI) index. RESULTS:Our sample was mostly female (58%), ≥ 65 years old, White (82%), and without radiographic knee osteoarthritis (50%). At the visit before a KR, Kellgren-Lawrence (KL) grades (ordinal scale; AUC 0.88, NRI 1.12, IDI 0.11), the alternate definition of esKOA (AUC 0.84, NRI 1.16, IDI 0.12), and a model with every component of esKOA (AUC 0.91, NRI 1.30, IDI 0.17) had the best performances. During the year before a KR, change in esKOA status (alternate definition) had the best performance (AUC 0.86, NRI 1.24, IDI 0.12). CONCLUSION:Radiographic severity may be a screening tool to find a knee that will likely receive a KR. However, esKOA may be an ideal outcome in clinical trials because a change in esKOA state predicts future KR.