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疼痛轨迹定义膝关节骨关节炎亚组:一项前瞻性观察研究。

Pain trajectory defines knee osteoarthritis subgroups: a prospective observational study.

作者信息

Radojčić Maja R, Arden Nigel K, Yang Xiaotian, Strauss Victoria Y, Birrell Fraser, Cooper Cyrus, Kluzek Stefan

机构信息

Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, United Kingdom.

Centre for Sport, Exercise and Osteoarthritis Research Versus Arthritis, University of Oxford, Oxford, United Kingdom.

出版信息

Pain. 2020 Dec;161(12):2841-2851. doi: 10.1097/j.pain.0000000000001975.

Abstract

Knee osteoarthritis (OA) is a heterogeneous disease, and identification of its subgroups/phenotypes can improve patient treatment and drug development. We aimed to identify homogeneous OA subgroups/phenotypes using pain development over time; to understand the interplay between pain and functional limitation in time course; and to investigate subgroups' responses to available pharmacological and surgical treatments. We used group-based trajectory modelling to identify pain trajectories in the phase-3 VIDEO trial (n = 474, 3-year follow-up) and also in the Osteoarthritis Initiative cohort study (n = 4796, 9-year follow-up). We extended trajectory models by (1) fitting dual trajectories to investigate the interplay between pain and functional limitation over time, and (2) including analgesic use as a time-varying covariate. Also, we investigated the relationship between trajectory groups and knee replacement in regression models. We identified 4 pain trajectory groups in the trial and 6 in the cohort. These overlapped and led us to define 4 OA phenotypes: low-fluctuating, mild-increasing, moderate-treatment-sensitive, and severe-treatment-insensitive pain. Over time, functional knee limitation followed the same trajectory as pain with almost complete concordance (94.3%) between pain and functional limitation trajectory groups. Notably, we identified a phenotype with severe pain that did not benefit from available treatments, and another one most likely to benefit from knee replacement. Thus, knee OA subgroups/phenotypes can be identified based on patients' pain experiences in studies with long and regular follow-up. We provided a robust approach, reproducible between different study designs, which informs clinicians about symptom development and delivery of treatment options and opens a new avenue toward personalized medicine in OA.

摘要

膝关节骨关节炎(OA)是一种异质性疾病,识别其亚组/表型可改善患者治疗和药物研发。我们旨在利用疼痛随时间的发展来识别同质的OA亚组/表型;了解疼痛与功能受限在时间进程中的相互作用;并研究亚组对现有药物和手术治疗的反应。我们使用基于群体的轨迹模型在3期VIDEO试验(n = 474,3年随访)以及骨关节炎倡议队列研究(n = 4796,9年随访)中识别疼痛轨迹。我们通过以下方式扩展轨迹模型:(1)拟合双轨迹以研究疼痛与功能受限随时间的相互作用,以及(2)将镇痛药物使用作为随时间变化的协变量纳入。此外,我们在回归模型中研究了轨迹组与膝关节置换之间的关系。我们在试验中识别出4个疼痛轨迹组,在队列中识别出6个。这些轨迹组相互重叠,使我们定义了4种OA表型:低波动、轻度增加、中度治疗敏感和重度治疗不敏感疼痛。随着时间的推移,膝关节功能受限与疼痛遵循相同的轨迹,疼痛和功能受限轨迹组之间几乎完全一致(94.3%)。值得注意的是,我们识别出一种严重疼痛的表型,其无法从现有治疗中获益,而另一种表型最有可能从膝关节置换中获益。因此,在长期定期随访的研究中,可以根据患者的疼痛经历识别膝关节OA亚组/表型。我们提供了一种强大的方法,在不同研究设计之间具有可重复性,可为临床医生提供有关症状发展和治疗选择的信息,并为OA的个性化医疗开辟了一条新途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d70/7654950/66163c01840d/jop-161-2841-g001.jpg

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