MEDIAL FIXED JSW TRAJECTORIES: PREDICTORS OF TRAJECTORIES AND THEIR ASSOCIATION WITH THE RISK OF KNEE REPLACEMENT

Osteoarthritis imaging Pub Date : 2026-01-01 Epub Date: 2026-06-20 DOI:10.1016/j.ostima.2026.100420
C.K. Kwoh, R. Tang, E.J. Bedrick, J. Crawmer, Z. Li, J. Liew, T. Neogi, X. Sun, J. Duryea
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引用次数: 0

Abstract

INTRODUCTION

Loss of JSW is a hallmark of knee OA structural progression, and knee replacement (KR) is considered by regulatory agencies as a hard clinical endpoint in knee OA DMOAD clinical trials. There has been limited longitudinal investigation of JSW trajectories and their association with the risk of KR, however. In addition, identification of predictors of worse vs. better JSW loss trajectories may help identify potential targets for therapeutic interventions and may also be useful for selecting more homogenous study populations.

OBJECTIVE

This study aimed to 1) identify distinct JSW trajectories; 2) identify predictors of different rates of change in medial fixed JSW (fJSW) trajectories; and 3) examine the association between JSW trajectories and the risk of KR.

METHODS

Knees (n = 2862) with available baseline MRI Osteoarthritis Knee Scores (MOAKS) from OAI were included. Observations collected after KR were excluded. Medial fJSW at 25% of femur width (i.e., x=0.250) was assessed longitudinally at baseline and each follow-up visit (i.e., 12, 24, 36, 48, 72, 96, and 120 months) to construct change-from-baseline JSW trajectories. Latent Class Mixed Models (LCMM) were employed to classify knees into two clusters having distinct fJSW trajectories, with (fJSW) change from baseline as the outcome and quadratic year term as the predictor, while jointly identifying predictors of latent class membership within the model. Covariates included demographic, clinical, psychosocial and imaging features. The response covariance matrix was allowed to be different for each latent class. Kaplan-Meier curves were used to illustrate time to KR for each fJSW trajectory cluster, and differences between clusters were assessed using the log-rank test.

RESULTS

Two fJSW trajectory clusters were identified: a faster progressive trajectory (n = 824) and a slower progressive trajectory (n = 2038) (Figure 1). Predictors of membership in the faster progressive trajectory included meniscal extrusion, effusion-synovitis/Hoffa synovitis, cartilage surface/depth damage, larger bone marrow lesion (BML) size, and being overweight/having obesity (i.e., BMI > 25) (Figure 2). The faster progressive trajectory was also associated with a higher risk of KR (p < 2e-16)

CONCLUSION

We have identified two distinct JSW trajectories that were associated with MRI-detected structural damage and specific demographic and clinical features. The faster progressive trajectory was associated with an increased risk of KR. Risk factors for the faster trajectory may represent suitable targets for interventions aimed at preventing KR.
内侧固定JSW轨迹:轨迹的预测因子及其与膝关节置换术风险的关联
JSW的丢失是膝关节OA结构进展的标志,膝关节置换术(KR)被监管机构认为是膝关节OA DMOAD临床试验的硬性临床终点。然而,关于JSW轨迹及其与KR风险之间关系的纵向调查有限。此外,鉴别JSW损失轨迹好坏的预测因素可能有助于确定治疗干预的潜在目标,也可能有助于选择更均匀的研究人群。本研究旨在1)识别不同的JSW轨迹;2)确定内侧固定JSW (fJSW)轨迹不同变化率的预测因子;3)检查JSW轨迹与kr风险之间的关系。方法纳入具有OAI可用基线MRI骨关节炎膝关节评分(MOAKS)的患者(n = 2862)。排除KR之后收集的观测。在基线和每次随访(即12、24、36、48、72、96和120个月)时纵向评估股骨宽度25%处内侧fJSW(即x=0.250),以构建从基线变化的JSW轨迹。使用潜类混合模型(LCMM)将膝关节分为两个具有不同fJSW轨迹的聚类,以(fJSW)从基线的变化作为结果,以二次年为预测因子,同时在模型中共同确定潜在类隶属度的预测因子。协变量包括人口统计学、临床、社会心理和影像学特征。允许每个潜在类别的响应协方差矩阵不同。Kaplan-Meier曲线用于说明每个fJSW弹道簇到达KR的时间,并使用log-rank检验评估簇之间的差异。结果鉴定出两组fJSW轨迹:快速进展轨迹(n = 824)和缓慢进展轨迹(n = 2038)(图1)。属于快速进展轨迹的预测因素包括半月板挤压、积液性滑膜炎/Hoffa滑膜炎、软骨表面/深度损伤、较大的骨髓病变(BML)大小、超重/肥胖(即BMI >; 25)(图2)。更快的进展轨迹也与更高的KR风险相关(p < 2e-16)结论:我们已经确定了两种不同的JSW轨迹,它们与mri检测到的结构损伤以及特定的人口统计学和临床特征相关。更快的进展轨迹与KR的风险增加有关。更快轨迹的危险因素可能是预防KR干预的合适目标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Osteoarthritis imaging
Osteoarthritis imaging Radiology and Imaging
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