title: Predicting chronic low-back pain based on pain trajectories in patients in an occupational setting: an exploratory analysis.
abstract: This study aimed to (i) identify subpopulations of patients in an occupational setting who will still have or develop chronic low-back pain (LBP) and (ii) evaluate a previously developed prediction model based on the determined subpopulations.
  
  
  
  In this prospective cohort, study data were analyzed from three merged randomized controlled trials, conducted in an occupational setting (N=622). Latent class growth analysis (LCGA) was used to distinguish patients with a different course of pain intensity measured over 12 months. The determined subpopulations were used to derive a definition for chronic LBP and evaluate an existing model to predict chronic LBP.
  
  
  
  The LCGA model identified three subpopulations of LBP patients. These were used to define recovering (353) and chronic (269) patients. None of the interventions showed a relevant treatment effect over another but the rate of decline in symptoms during the first months of the intervention seems to predict recovery. The prediction model, based on this dichotomous outcome, with the variables pain intensity, kinesiophobia and a clinically relevant change in pain intensity and functional status in the first three months, showed a bootstrap-corrected performance with an area under the operating characteristic curve (AUC) of 0.75 and explained variance of 0.26.
  
  
  
  In an occupational setting, different subpopulations of chronic LBP patients could be identified using LCGA. The prediction model based on these subpopulations showed a promising predictive performance.
authors.affiliation: VU University medical centre, PO Box 7057, 1007 MB Amsterdam, The Netherlands. gpanken@hetnet.nl.
authors.forename: Guus
authors.initials: G
authors.lastname: Panken
authors.forename: Trynke
authors.initials: T
authors.lastname: Hoekstra
authors.forename: Arianne
authors.initials: A
authors.lastname: Verhagen
authors.forename: Maurits
authors.initials: M
authors.lastname: van Tulder
authors.forename: Jos
authors.initials: J
authors.lastname: Twisk
authors.forename: Martijn W
authors.initials: MW
authors.lastname: Heymans
mesh_terms: D000328:Adult; D059350:Chronic Pain; D004185:Disability Evaluation; D005260:Female; D006801:Humans; D017116:Low Back Pain / Q000628:therapy*; D008297:Male; D015233:Models, Statistical; D016272:Occupational Health; D010147:Pain Measurement / Q000706:statistics & numerical data; D011237:Predictive Value of Tests; D011446:Prospective Studies; D020127:Recovery of Function; D018582:Sick Leave; D011795:Surveys and Questionnaires