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Osteoarthritis Cartilage. 2014 Dec;22(12):2041-50. doi: 10.1016/j.joca.2014.09.026. Epub 2014 Oct 8.

Pain trajectory groups in persons with, or at high risk of, knee osteoarthritis: findings from the Knee Clinical Assessment Study and the Osteoarthritis Initiative.

Author information

1
Arthritis Research UK Primary Care Centre, Research Institute for Primary Care and Health Sciences, Keele University, Keele, Staffordshire ST5 5BG, United Kingdom. Electronic address: e.nicholls@keele.ac.uk.
2
Arthritis Research UK Primary Care Centre, Research Institute for Primary Care and Health Sciences, Keele University, Keele, Staffordshire ST5 5BG, United Kingdom. Electronic address: e.thomas@keele.ac.uk.
3
Arthritis Research UK Primary Care Centre, Research Institute for Primary Care and Health Sciences, Keele University, Keele, Staffordshire ST5 5BG, United Kingdom. Electronic address: d.van.der.windt@keele.ac.uk.
4
Arthritis Research UK Primary Care Centre, Research Institute for Primary Care and Health Sciences, Keele University, Keele, Staffordshire ST5 5BG, United Kingdom. Electronic address: p.r.croft@keele.ac.uk.
5
Arthritis Research UK Primary Care Centre, Research Institute for Primary Care and Health Sciences, Keele University, Keele, Staffordshire ST5 5BG, United Kingdom. Electronic address: g.m.peat@keele.ac.uk.

Abstract

OBJECTIVE:

The authors aimed to characterize distinct trajectories of knee pain in adults who had, or were at high risk of, knee osteoarthritis using data from two population-based cohorts.

METHOD:

Latent class growth analysis was applied to measures of knee pain severity on activity obtained at 18-month intervals for up to 6 years between 2002 and 2009 from symptomatic participants aged over 50 years in the Knee Clinical Assessment Study (CAS-K) in the United Kingdom. The optimum latent class growth model from CAS-K was then tested for reproducibility in a matched sample of participants from the Osteoarthritis Initiative (OAI) in the United States.

RESULTS:

A 5-class linear model produced interpretable trajectories in CAS-K with reasonable goodness of fit and which were labelled "Mild, non-progressive" (N = 201, 35%), "Progressive" (N = 162, 28%), "Moderate" (N = 124, 22%) "Improving" (N = 68, 12%), and "Severe, non-improving" (N = 15, 3%). We were able to reproduce "Mild, non-progressive", "Moderate", and "Severe, non-improving" classes in the matched sample of participants from the OAI, however, absence of a "Progressive" class and instability of the "Improving" classes in the OAI was observed.

CONCLUSIONS:

Our findings strengthen the grounds for moving beyond a simple stereotype of osteoarthritis as "slowly progressive". Mild, non-progressive or improving symptom trajectories, although difficult to reproduce, can nevertheless represent a genuinely favourable prognosis for a sizeable minority.

KEYWORDS:

Knee; Latent class growth analysis; Longitudinal; Osteoarthritis; Pain; Trajectories

PMID:
25305072
PMCID:
PMC4256061
DOI:
10.1016/j.joca.2014.09.026
[Indexed for MEDLINE]
Free PMC Article

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