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Objectives We aimed to identify determinants of health-related quality of life (HRQoL) and global functioning and health (GH) in axial SpA (axSpA), peripheral SpA (pSpA) and (PsA). Methods The ASAS-perSpA study data were analysed. Models for the three patient groups were run separately to explore factors associated with HRQoL and GH, assessed by EQ-5D and ASAS-HI, respectively. Results The analyses included 4185 patients: 2719 with axSpA, 433 with pSpA, and 1033 with PsA. In axSpA, disease activity (β = –0.061), physical function (β = –0.041), female sex (β = –0.019) and fibromyalgia (FM) (β = –0.068) were associated with worse HRQoL; age (β = 0.001) and university education (β = 0.014) were associated with better HRQoL. In pSpA, disease activity (β = –0.04) and physical function (β = –0.054) were associated with worse HRQoL. In PsA, disease activity (β = –0.045), physical function (β = –0.053), axial disease (β = –0.041) and female sex (β = –0.028) were associated with worse HRQoL. In axSpA, disease activity (β = 0.889), physical function (β = 0.887), peripheral disease (β = 0.564), female sex (β = 0.812) and FM (β = 1.639) were associated with worse GH; age (β = –0.013) and university education (β = –0.274) were associated with better GH. In pSpA, physical function (β = 1.142) and female sex (β = 1.060) were associated with worse GH; university education (β = –0.611) was associated with better GH. In PsA, disease activity (β = 0.703), physical function (β = 1.025), axial involvement (β = 0.659), female sex (β = 0.924) and FM (β = 1.387) were associated with worse GH; age (β = –0.024) and university education (β = –0.856) were associated with better GH. Conclusion Disease activity and physical function are major HRQoL and GH determinants across SpA types, and clinical characteristics and sociodemographic factors play an important role, highlighting the importance of a holistic approach for individual patients.
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Santos et al. (2023) studied this question.
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