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Refinement of the classification criteria for early-stage knee osteoarthritis to enrich for progressors
Abstract   Peer reviewed

Refinement of the classification criteria for early-stage knee osteoarthritis to enrich for progressors

A. Mahmoudian, M. Englund, S. Bierma-Zeinstra, M. Kloppenburg, S. Lohmander and F.P. Luyten
Osteoarthritis and Cartilage, Vol.28
04/01/2020
04/2020
DOI: https://doi.org/10.1016/j.joca.2020.02.592

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Abstract

Purpose: Classification criteria and clinical management guidelines have been issued for established osteoarthritis of the knee. However, patients who fulfill these criteria commonly have substantial structural damage, altered biomechanics, and altered pain processing due to chronic pain, which make disease modification challenging. To potentially facilitate a greater likelihood of favorable response to new disease-modifying therapies, recruitment of patients at an earlier stage of their disease into clinical trials may be a key stratification strategy. Hence, there is a need to develop generally and widely accepted classification criteria for early-stage knee OA. In view of this, we have proposed new classification criteria for early-stage knee OA (EskOA) (Box 1), which are now being further refined, in this report in particular tested for enrichment for clinical and structural progression. Methods: As an initial step, we took a classical statistical approach looking into an existing cohort with longitudinal data of knee OA subjects. For this first round of analyses Osteoarthritis Initiative (OAI) data was selected. The OAI comprises data of 4796 men and women aged 45-79 years with or at risk for knee OA at baseline. OAI cohort comprises of 3 sub-cohorts of progression (n = 1390), incident (n=3284), and non-exposed control groups (n=122). Data from all 3 sub-cohorts were included in this analyses. Knees were excluded if they had: 1) missing data (KOOS sub-scales, X-ray scores, or clinical examination); 2) established radiological OA as defined by Kellgren & Lawrence (K&L) grade ≥ 2. Remaining subjects were divided into two groups of EsKOA and control, on the basis of the presence/absence of EsKOA (Box 1). Logistic regression analysis was used to evaluate the predictive performance of EsKOA criteria for medial/lateral compartment joint space narrowing (JSN) at 48 months (by 1 grade as defined by OAI) (structural progression), as well as the progression towards K&L grade 2 with JSN at any time point from baseline. Pain deterioration (clinical progression), as measured by KOOS (10 score drop over 48 months), was used separately as a patient-relevant outcome measure. We performed additional analyses following the same criteria but exploring some other variables including the average KOOS4, additional clinical examination findings such as the presence of “effusion” and/or “Heberden’s nodes”. Results: We identified 1033 knees from OAI fulfilling the criteria of EsKOA (Box1), and 5046 knees as controls (neither fulfilling the EsKOA, nor the exclusion criteria). The female to male ratio was significantly higher in the EsKOA group compared to controls. Also, those with EsKOA were on average slightly older and had higher body mass index (BMI) vs controls (mean [SD] age: 59.2 [8.9] years vs. 60.2 [9.1] and mean [SD] BMI 28.3 [7.0] vs. 26.8 [6.0]). Our results indicate that expanding clinical findings including joint effusion and/or Heberden’s nodes can marginally improve the enrichment only in structural progressors. Replacing scoring of the 4 separate KOOS domains by an average KOOS4 score resulted in enrichment for both clinical and structural progressors. Conclusions: The proposed EsKOA classification criteria showed encouraging performance characteristics using longitudinal OAI data. Exploring additional variables such as average KOOS and some clinical examination findings appear to improve the predictive performance of the proposed classification criteria in early stage knee OA for both clinical and structural progression. Testing for more variables or combinations thereof and screening in other databases is ongoing.

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