Clustering multi-site pain diagrams

Background and aims: Studies show that there are clinical differences between multi-site pain and mono-site pain [1]. There is a strong linear association between the number of pain sites and reduction in overall health and higher psychological distress [2]. Previous research has mostly used few pain sites and arbitrary grouping criteria. The purpose of this study was to (a) identify subgroups of back pain patients on the basis of their pain distribution, and (b) describe their cross-sectional characteristics.

Methods: Adult back pain patients were included from the Spine Centre of Southern Denmark after completing an electronic questionnaire and undergoing a physical examination. Probabilistic data mining was used to identify subgroups of pain patterns across 46 areas of a standardized pain chart [3]. The clinical characteristics of these subgroups were described in the health domains of pain and psychological factors. Differences between subgroups were tested using analysis of variance and post-hoc pair-wise comparisons (pResults: 21.123 patients were included. Five patterns of pain distribution were identified: whole spine pain (13%), diffuse LBP + leg pain (23%), whole body pain (7%), local MBP/Neck pain (19%), local LBP (38%).
There are statistically significant baseline differences between these subgroups on all measured parameters in all health domains. Post-hoc analysis in pain intensity only shows statistical significance when pair-wise compared with Whole body pain or Diffuse low back + leg pain. Activity limitation was significant across all subgroups, except between Local MBP/neck vs. Local LBP (p = 0.29). Self-reported social isolation was prominent for multi-sited pain. Overall, patients in subgroups with a larger number of pain sites presented higher scores on all psychological factors. Although many differences were not clinically important in size, some were, especially when comparing multi-site pain and localized pain. Between patients with whole body pain and local MBP/NP the effect size was moderate (> 0.5) in self-reported social isolation and depression.
Another noticeable finding is that local LBP and local MBP/NP have closely similar baseline characteristics.
Conclusions: These findings show that five pain patterns were associated with many baseline differences between back pain patients. Mono-site and multi-site pain subgroups could be differentiated and mono-site pain subgroups show commonalities. There appears to be important and unique information, at a group level, in the pain distribution of patients with back pain.
References:
[1] Hartvigsen J, Natvig B, Ferreira M. Is it all about a pain in the back? Best Pract Res Clin Rheumatol. 2013 Oct;27(5):613-23. doi: 10.1016/j.berh.2013.09.008. Epub 2013 Oct 5. PMID: 24315143.
[2] Kamaleri Y, Natvig B, Ihlebaek CM, Benth JS, Bruusgaard D. Number of pain sites is associated with demographic, lifestyle, and health-related factors in the general population. European Journal of Pain 2008;12:742–8.
[3] Margolis RB, Tait RC, Krause SJ. A rating system for use with patient pain drawings. Pain. 1986 Jan;24(1):57-65. doi: 10.1016/0304-3959(86)90026-6. PMID: 2937007.

Ethical Permissions: Godkendt hos Regionen og Team Jura

Relevance for Patient Care: Early identification and differentiation of subgroups may provide more help when informing patients about prognosis, fitting treatment plans to match profiles, and guiding the need for referrals to specialist services in a timely fashion.