Objectives: To identify distinct pain trajectories over 10.7 years and to examine predictors of identified pain trajectories in an older population and those with radiographic knee osteoarthritis (ROA).

Methods: 963 participants (aged 50-80 years) from a population-based cohort had baseline demographic, psychological, lifestyle and comorbidities data collected. T1-and T2-weighted magnetic resonance imaging (MRI) of the right knee was performed to measure knee structural pathology-cartilage defects, bone marrow lesions (BMLs) and effusion-synovitis. Group-based trajectory modelling (GBTM) was applied to identify trajectories of knee pain over 10.7 years measured by Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC).

Results: Three distinct pain trajectories were defined: 'Minimal pain' (n = 501, 52%), 'Mild pain' (n = 329, 34%) and 'Moderate pain' (n = 165, 14%). In multivariable analysis, having cartilage defects, BMLs and effusion-synovitis were associated with an increased risk of being in the 'Mild pain' (relative risk [RR]: 1.40 to 1.92) and 'Moderate pain' trajectory (RR: 1.72 to 2.26), compared with the 'Minimal pain' trajectory. Being obese and having more painful sites were associated with 'Mild pain' and 'Moderate pain' trajectories, while unemployment, lower education level and presence of emotional problems were associated with 'Moderate pain' trajectory group. Similar results were found for those with ROA.

Conclusion: Distinct pain trajectories identified suggest that homogeneous subgroups exist, which might be useful for phenotypic assessment for pain management, particularly in knee osteoarthritis. Structural pathology was associated with worse pain trajectories, suggesting that peripheral stimuli are critical for the development and maintenance of pain severity. Environmental and psychological factors may exacerbate pain perception.

Item Type:	Refereed Article
Keywords:	knee osteoarthritis, MRI, pain, risk factor, trajectory
Research Division:	Biomedical and Clinical Sciences
Research Group:	Clinical sciences
Research Field:	Rheumatology and arthritis
Objective Division:	Health
Objective Group:	Clinical health
Objective Field:	Clinical health not elsewhere classified
UTAS Author:	Pan, F (Dr Feng Pan)
UTAS Author:	Tian, J (Dr Jing Tian)
UTAS Author:	Aitken, D (Associate Professor Dawn Aitken)
UTAS Author:	Jones, G (Professor Graeme Jones)
ID Code:	128162
Year Published:	2018
Web of Science® Times Cited:	3
Deposited By:	Menzies Institute for Medical Research
Deposited On:	2018-09-06
Last Modified:	2019-03-07
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