Determinants of health-related quality of life across the spectrum of connective tissue diseases using latent profile analysis: Results from the LEAP cohort

Objectives
Poor health-related quality of life (HR-QoL) is well recognised in patients with connective tissue diseases (CTD). We hypothesised that subgroups of patients across the spectrum of CTD experience different HR-QoL patterns, and aimed to determine patient-level characteristics associated with these different subgroups.

Methods
Using the eight continuous domains of the Medical Outcomes Study Short-Form 36 (SF-36) questionnaire we performed data-driven clustering to derive latent profiles (LP) of patients with distinct HR-QoL patterns. Multivariable ordinal logistic regression was used to determine patient-level characteristics associated with each HR-QoL subgroup identified.

Results
309 CTD patients completed the SF-36 questionnaire. The most impaired SF-36 domains in each disease group were vitality, general health and bodily pain. The physical component of the SF-36 was consistently more impaired compared with the mental component, with similar scores across disease groups.

Three latent profiles were identified with poor (n = 89; 29%), average (n = 190; 61.4%) and excellent (n = 30; 9.7%) HR-QoL. LP were not associated with diagnostic grouping or autoantibody profiles. Black background (OR 0.22 [95% CI 0.08–0.63]), Indo-Asian background (0.39 [0.19–0.78]), concomitant fibromyalgia (0.40 [0.20–0.78]), sicca symptoms (0.56 [0.32–0.98]) and multi-morbidity (Charlson Comorbidity Index, 0.81 [0.67–0.97]) were associated with the ‘poor’ HR-QoL LP.

Conclusion
Distinct HR-QoL subgroups exist that are not primarily driven by the specific diagnosis or autoantibody profiles. We identified a number of key demographic and clinical factors associated with poor HR-QoL. These factors need to be addressed across the whole CTD spectrum as part of a holistic management approach aimed at improving overall patient outcomes.