Novel approach to characterising individuals with low back-related leg pain: cluster identification with latent class analysis and 12-month follow-up.

Stynes, Siobhán; Konstantinou, Kika; Ogollah, Reuben; Hay, Elaine M.; Dunn, Kate M.

Abstract

Traditionally, low back-related leg pain (LBLP) is diagnosed clinically as referred leg pain or sciatica (nerve root involvement). However, within the spectrum of LBLP, we hypothesised that there may be other unrecognised patient subgroups. This study aimed to identify clusters of patients with LBLP using latent class analysis and describe their clinical course. The study population was 609 LBLP primary care consulters. Variables from clinical assessment were included in the latent class analysis. Characteristics of the statistically identified clusters were compared, and their clinical course over 1 year was described. A 5 cluster solution was optimal. Cluster 1 (n = 104) had mild leg pain severity and was considered to represent a referred leg pain group with no clinical signs, suggesting nerve root involvement (sciatica). Cluster 2 (n = 122), cluster 3 (n = 188), and cluster 4 (n = 69) had mild, moderate, and severe pain and disability, respectively, and response to clinical assessment items suggested categories of mild, moderate, and severe sciatica. Cluster 5 (n = 126) had high pain and disability, longer pain duration, and more comorbidities and was difficult to map to a clinical diagnosis. Most improvement for pain and disability was seen in the first 4 months for all clusters. At 12 months, the proportion of patients reporting recovery ranged from 27% for cluster 5 to 45% for cluster 2 (mild sciatica). This is the first study that empirically shows the variability in profile and clinical course of patients with LBLP including sciatica. More homogenous groups were identified, which could be considered in future clinical and research settings.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal.

Citation

Stynes, S., Konstantinou, K., Ogollah, R., Hay, E. M., & Dunn, K. M. (2018). Novel approach to characterising individuals with low back-related leg pain: cluster identification with latent class analysis and 12-month follow-up. PAIN, 159(4), https://doi.org/10.1097/j.pain.0000000000001147

• Journal Article Type: Article
• Acceptance Date: Dec 22, 2017
• Publication Date: Jan 9, 2018
• Journal: Pain
• Print ISSN: 0304-3959
• Publisher: Lippincott, Williams & Wilkins
• Peer Reviewed: Peer Reviewed
• Volume: 159
• Issue: 4
• DOI: https://doi.org/10.1097/j.pain.0000000000001147
• Keywords: sciatica; low back-related leg pain; latent class analysis; primary care; clinical course
• Publisher URL: https://insights.ovid.com/crossref?an=00006396-900000000-99063