Determining one-year trajectories of low back related leg pain in primary care patients: growth mixture modelling of a prospective cohort study

Dunn; Stynes

Abstract

OBJECTIVE
The clinical presentation and outcome of patients with back and leg pain in primary care are heterogeneous and may be better understood by identification of homogeneous and clinically meaningful subgroups. Subgroups of patients with different back pain trajectories have been identified, but little is known about the trajectories for patients with back-related leg pain. This study sought to identify distinct leg pain trajectories, and baseline characteristics associated with membership of each group, in primary care patients.

METHODS: Monthly data on leg pain intensity were collected over 12 months for 609 patients participating in a prospective cohort study of adult patients seeking healthcare for low back and leg pain including sciatica, of any duration and severity, from their general practitioner. Growth mixture modelling was used to identify clusters of patients with distinct leg pain trajectories. Trajectories were characterised using baseline demographic and clinical examination data. Multinomial logistic regression was used to predict latent class-membership with a range of covariates. RESULTS: Four clusters were identified: (1) improving mild pain (58%), (2) persistent moderate pain (26%), (3) persistent severe pain (13%), and (4) improving severe pain (3%). Clusters showed statistically significant differences with a number of baseline characteristics.

CONCLUSION: Four trajectories of leg pain were identified. Clusters 1, 2 and 3 were generally comparable to back pain trajectories, while cluster 4, with major improvement in pain, is infrequently identified. Awareness of such distinct patient groups improves understanding of the course of leg pain and may provide a basis of classification for intervention. This article is protected by copyright. All rights reserved.

Citation

Dunn, & Stynes. (2018). Determining one-year trajectories of low back related leg pain in primary care patients: growth mixture modelling of a prospective cohort study. Arthritis Care and Research, 1840-1848. https://doi.org/10.1002/acr.23556

• Acceptance Date: Mar 25, 2018
• Publication Date: Dec 1, 2018
• Journal: Arthritis Care and Research
• Print ISSN: 2151-464X
• Publisher: Wiley
• Pages: 1840-1848
• DOI: https://doi.org/10.1002/acr.23556
• Keywords: leg pain; pain trajectories; sciatica; primary care; growth mixture modelling; prospective
• Publisher URL: https://doi.org/10.1002/acr.23556