Background & Aims

The efficacy of first-line chronic pain treatment is unsatisfactory in over 50% of individuals [1] probably due to the considerable heterogeneity of underlying pathomechanisms. Identifying more homogeneous subgroups of individuals with chronic pain based on common pathomechanisms might enable more targeted treatment strategies. Previously, our group clustered individuals based on sensory phenotypes (hypo- and hypersensitivities) in painful and pain-free body areas. While these clusters partly related to spontaneous pain intensity [2], other groups observed significant hypersensitivities in individuals with certain pathological conditions without spontaneous pain (e.g., small fiber neuropathy) [3]. This observation supports the notion that sensory function alone do not fully explain chronic pain mechanisms. We therefore aimed to cluster individuals with and without chronic pain based on an extended biopsychosocial model [4].

Methods

Sixty-one low back pain (LBP), 21 complex regional pain syndrome (CRPS), 19 spinal cord injury (SCI) patients with neuropathic pain, and 63 age and sex-matched healthy controls (HC) were recruited. Information on age, sex, education, living status, general health, physical activity [5], interoceptive awareness [6], and psychological factors (anxiety, depression [7], and pain catastrophizing [8]) was gathered using online questionnaires. Quantitative sensory testing (QST [9]) was performed in the most painful and a pain-free, remote area. Pain modulation capacities were assessed by conditioned pain modulation, experimental pain habituation and multimodal temporal summation of pain paradigms as additional relevant biological measures. For a visual inspection of potential clusters with differential pathomechanisms, the gathered biopsychosocial features were used to perform a Uniform Manifold Approximation and Projection (UMAP [10]) that was compared to a UMAP only including the QST data.

Results

The UMAP analysis with all biopsychosocial features demonstrated superior performance in differentiating the four cohorts (LBP, CRPS, SCI, and HC) compared to the QST-based UMAP. While the QST-based UMAP was effective in distinguishing individuals with SCI and CRPS, it failed to clearly differentiate between the LBP and HC cohorts. In contrast, the UMAP with all biopsychosocial features, despite some overlap, showed a discernible gradient between the LBP and HC cohorts. Most importantly, the UMAP with all biopsychosocial features was particularly effective in separating individuals in terms of maximal spontaneous pain intensity perceived in the last four weeks. Although UMAP inherently does not provide direct feature importance metrics, we conducted a sensitivity analysis to infer feature importance indirectly. It highlighted that pain modulation in the pain-free area, psychological factors, and education might play a pivotal role in defining subgroups within our dataset.

Conclusions

This study highlights the importance of a comprehensive biopsychosocial approach in understanding chronic pain conditions and clustering of affected individuals. Our findings demonstrate that incorporating a wide range of biopsychosocial features, including pain modulatory, psychological and educational aspects, offers a more effective method for differentiating individuals with various chronic pain conditions (LBP, CRPS, SCI) and HC compared to methods only including the sensory function (i.e., QST). Most importantly, this biopsychosocial approach not only facilitated the identification of distinct pain cohorts but also provided insights into the varying levels of spontaneous pain intensity experienced by individuals with chronic pain.

References

1.Breivik H, Eisenberg E, O’Brien T. The individual and societal burden of chronic pain in Europe: The case for strategic prioritisation and action to improve knowledge and availability of appropriate care. BMC Public Health. 2013;13(1). doi:10.1186/1471-2458-13-1229
2.De Schoenmacker I, Sirucek L, Scheuren PS, et al. Sensory phenotypes in complex regional pain syndrome and chronic low back pain – Indication of common underlying pathomechanisms. Pain Rep. 2023;8(6):E1110. doi:10.1097/PR9.0000000000001110
3.Forstenpointner J, Ruscheweyh R, Attal N, et al. No pain, still gain (of function): the relation between sensory profiles and the presence or absence of self-reported pain in a large multicenter cohort of patients with neuropathy. Pain. 2021;162(3):718-727. doi:10.1097/j.pain.0000000000002058
4.Gatchel RJ, Peng YB, Peters ML, Fuchs PN, Turk DC. The biopsychosocial approach to chronic pain: scientific advances and future directions. Psychol Bull. 2007;133(4):581-624. doi:10.1037/0033-2909.133.4.581
5.Lee PH, Macfarlane DJ, Lam TH, Stewart SM. Validity of the international physical activity questionnaire short form (IPAQ-SF): A systematic review. International Journal of Behavioral Nutrition and Physical Activity. 2011;8. doi:10.1186/1479-5868-8-115
6.Mehling WE, Price C, Daubenmier JJ, Acree M, Bartmess E, Stewart A. The Multidimensional Assessment of Interoceptive Awareness (MAIA). PLoS One. 2012;7(11). doi:10.1371/journal.pone.0048230
7.Zigmond AS, Snaith RP. The Hospital Anxiety and Depression Scale. Acta psychiats scand. 1983;67:361-370. doi:10.1093/occmed/kqu024
8.Sullivan MJL, Bishop SR. The Pain Catastrophizing Scale: Development and Validation. J Physiother. 1995;7:524-332. doi:10.1016/s1836-9553(10)70047-3
9.Rolke R, Magerl W, Campbell KA, et al. Quantitative sensory testing: A comprehensive protocol for clinical trials. European Journal of Pain. 2006;10(1):77. doi:10.1016/j.ejpain.2005.02.003
10.McInnes L, Healy J, Melville J. UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction. Published online February 9, 2018. https://arxiv.org/abs/1802.03426

Presenting Author

Iara De Schoenmacker

Poster Authors

Iara De Schoenmacker

PhD

ETH Zurich

Lead Author

E-mail

Laura Sirucek

Balgrist University Hospital, University of Zurich

Lead Author

E-mail

Paulina Scheuren

University of British Columbia

Lead Author

E-mail

Robin Lütolf

PhD

Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich

Lead Author

E-mail

Lindsay Gorrell

MChiroprac

Balgrist University Hospital, University of Zurich

Lead Author

E-mail

Florian Brunner

MD PhD

Department of Physical Medicine and Rheumatology, Balgrist University Hospital, University of Zurich

Lead Author

E-mail

Armin Curt

MD

Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich

Lead Author

E-mail

Jan Rosner

MD

Balgirst University Hospital, Zurich

Lead Author

E-mail

Petra Schweinhardt

University of Zurich

Lead Author

E-mail

Michèle Hubli

Spinal Cord Injury Research Center

Lead Author

E-mail

Topics

  • Mechanisms: Psychosocial and Biopsychosocial