title: Pain trajectory groups in persons with, or at high risk of, knee osteoarthritis: findings from the Knee Clinical Assessment Study and the Osteoarthritis Initiative.
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.
  
  
  METHODS
  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.
authors.affiliation: 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.
authors.forename: E
authors.initials: E
authors.lastname: Nicholls
authors.affiliation: 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.
authors.forename: E
authors.initials: E
authors.lastname: Thomas
authors.affiliation: 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.
authors.forename: D A
authors.initials: DA
authors.lastname: van der Windt
authors.affiliation: 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.
authors.forename: P R
authors.initials: PR
authors.lastname: Croft
authors.affiliation: 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.
authors.forename: G
authors.initials: G
authors.lastname: Peat
mesh_terms: D018771:Arthralgia / Q000150:complications*; D018450:Disease Progression; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D020370:Osteoarthritis, Knee / Q000150:complications* / Q000175:diagnosis* / Q000453:epidemiology; D011446:Prospective Studies; D012306:Risk; D012720:Severity of Illness Index
keywords: Knee; Latent class growth analysis; Longitudinal; Osteoarthritis; Pain; Trajectories