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BMC Musculoskelet Disord. 2011 May 17;12:99. doi: 10.1186/1471-2474-12-99.

Clustering patients on the basis of their individual course of low back pain over a six month period.

Author information

1
The Karolinska Institutet, Institute of Environmental Medicine, Sweden. iben.axen@ki.se

Abstract

BACKGROUND:

Several researchers have searched for subgroups in the heterogeneous population of patients with non-specific low back pain (LBP). To date, subgroups have been identified based on psychological profiles and the variation of pain.

METHODS:

This multicentre prospective observational study explored the 6- month clinical course with measurements of bothersomeness that were collected from weekly text messages that were sent by 176 patients with LBP. A hierarchical cluster analysis, Ward's method, was used to cluster patients according to the development of their pain.

RESULTS:

Four clusters with distinctly different clinical courses were described and further validated against clinical baseline variables and outcomes. Cluster 1, a "stable" cluster, where the course was relatively unchanged over time, contained young patients with good self- rated health. Cluster 2, a group of "fast improvers" who were very bothered initially but rapidly improved, consisted of patients who rated their health as relatively poor but experienced the fewest number of days with bothersome pain of all the clusters. Cluster 3 was the "typical patient" group, with medium bothersomeness at baseline and an average improvement over the first 4-5 weeks. Finally, cluster 4 contained the "slow improvers", a group of patients who improved over 12 weeks. This group contained older individuals who had more LBP the previous year and who also experienced most days with bothersome pain of all the clusters.

CONCLUSIONS:

It is possible to define clinically meaningful clusters of patients based on their individual course of LBP over time. Future research should aim to reproduce these clusters in different populations, add further clinical variables to distinguish the clusters and test different treatment strategies for them.

PMID:
21586117
PMCID:
PMC3125255
DOI:
10.1186/1471-2474-12-99
[Indexed for MEDLINE]
Free PMC Article

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