OP0209-HPR NETWORKS OF FATIGUE, PAIN, AND BIOPSYCHOSOCIAL FACTORS IN PEOPLE WITH RHEUMATOID ARTHRITIS. THE NET-RMDS STUDY
Authors: R. Geenen, B. Gavilán-Carrera, F. Estevez-Lopez, L. Boschloo, M. Visser, J. Mcveigh, C. Hughes, R. J. O. Ferreira, L. Barbosa
Journal: Annals of the Rheumatic Diseases (2024)

<h3>Background:</h3> Fatigue and pain are part of a complex network of co-occurring biological, psychological, and social factors. Furthermore, the levels reflecting problems on these factors are assumed to differ between people with rheumatoid arthritis (RA). <h3>Objectives:</h3> In people with RA, to estimate a network of relationships between fatigue, pain, and seven other biopsychosocial factors (objective 1) and to describe subgroups (clusters) of people based on their levels on factors (objective 2). <h3>Methods:</h3> The protocol of this study was published [1]. People from patient associations collaborated in setting up the study, recruiting participants, and interpreting results. Participants were recruited in five European countries. Self-report measures of fatigue, pain and seven other biopsychosocial factors were assessed using numeric (0 to 10) rating scales. Factors were derived from literature and interviews with patients and health professionals in rheumatology including rheumatologists. Priority was given to factors that are modifiable by self-management or interventions. Estimation of the partial correlation network was done with LASSO regularization using the R package <i>mgm</i> (objective 1). K-means cluster analysis in SPSS was performed to parsimoniously allocate participants to clusters (objective 2). <h3>Results:</h3> Data from 189 people with RA without another rheumatic and musculoskeletal disease (RMD) from Ireland (n=44), the Netherlands (n=60), Portugal (n=42), Spain (n=8), the United Kingdom (n=16), and other countries (n=19) were analyzed. Other demographics were: 163 women, 26 men; mean age 51 (range 22 to 79) yrs.; education: primary (n=1), secondary (n=39), advanced (n=68), higher (n=81). Mean (SD) levels on the nine factors were: fatigue 6.4 (2.2), pain 5.1 (2.5), sleep problems 5.0 (2.7), disease activity 5.0 (2.5), inactive lifestyle 4.4 (2.7), lack of understanding 4.2 (3.2), unhealthy diet 3.6 (2.2), unhealthy body weight 3.6 (2.9), and psychological problems 3.6 (2.6). The network (see Figure 1) shows the estimated partial correlations (r<sub>p</sub>) of fatigue, pain and the other factors; zero correlations are not shown. The thickness of circles represents mean levels at the nine factors and thickness of connecting lines reflect the strength of partial correlations between these factors. Pain was associated with disease activity (r<sub>p</sub>=.71), fatigue (r<sub>p=</sub>.20), inactive lifestyle (r<sub>p=</sub>.06), and unhealthy body weight (r<sub>p=</sub>.03). Fatigue was associated with pain (r<sub>p=</sub>.20), sleep problems (r<sub>p=</sub>.27), lack of understanding (r<sub>p=</sub>.14), psychological problems (r<sub>p=</sub>.09), and unhealthy diet (r<sub>p=</sub>.04). Cluster analysis yielded six clusters (see Table 1). Fatigue levels in all clusters and pain in four clusters were medium (4 to 6) to high (&gt;6). Cluster 2 showed low levels on the seven other factors and cluster 5 high levels on all but one of the seven other factors. The four remaining groups showed varied levels on the other factors. <h3>Conclusion:</h3> The network model highlights that pain was associated with other factors than fatigue. Cluster analysis evidenced individual variations in the perceived severity of these biopsychosocial factors. For management, the network model in the whole sample indicates that interventions may be somewhat different for pain and fatigue, while cluster analysis indicates that specific subgroups of patients with RA may benefit from an approach focused on distinct factors. <h3>REFERENCES:</h3> [1] Gavilán-Carrera et al. NET-RMDs study: networks of fatigue and pain in rheumatic and musculoskeletal diseases – protocol for an international cross-sectional study. BMJ Open 2022; 12(11), e061099. <b>Table 1.</b> <h3>Acknowledgements:</h3> The authors gratefully acknowledge all participants, the collaborating representatives from patient associations, and the European alliance for associations of rheumatology (EULAR) for funding the project (HPR045). <h3>Disclosure of Interests:</h3> <b>None declared.</b>