Connective tissue diseases (CTDs) can be clustered into distinct subgroups that are not primarily driven by a specific diagnosis or autoantibody profile, according to the results a study published in Rheumatology (Oxford).
Subgroups of patients across the spectrum of CTDs experience different HRQOL patterns, regardless of their clinical diagnosis. Researchers conducted a prospective Lupus Extended Autoimmune Phenotype (LEAP) study to determine patient-level characteristics associated with the different subgroups.
Eight continuous domains of the Medical Outcomes Study 36-item Short Form (SF-36) questionnaire were used to perform data-driven clustering, in an effort to derive latent profiles among individuals with distinct patterns of HRQOL. The 8 domains on the SF-36 included physical function, role physical, bodily pain, general health, vitality, social functioning, role emotional, and mental health. All scores ranged from 0 to 100, with higher scores indicative of better HRQOL.
All patients were enrolled into the LEAP cohort study from the Manchester University National Health Service (NHS) Foundation Trust and the Northern Care Alliance NHS Foundation Trust between May 2014 and June 2019.
Individuals with an established CTD diagnosis and clinically stable disease were eligible for study inclusion if they had at least 1 clinical feature of a CTD and 1 or more antibodies within the antinuclear antibody spectrum.
Based on a diagnosis by a rheumatologist, patients were classified into 4 groups: systemic lupus erythematosus (SLE); primary Sjögren syndrome; undifferentiated connective tissue disease; and idiopathic inflammatory myopathy, systemic sclerosis, or an overlap syndrome that included mixed connective tissue disease.
A total of 309 individuals with CTDs completed the SF-36 questionnaire. In each of the CTD subgroups, the most impaired SF-36 domains included vitality, general health, and bodily pain. Overall, the physical vs mental components of HRQOL on the SF-36 questionnaire were consistently more impaired, with similar scores reported across the disease groups.
Researchers identified 3 latent profiles associated with poor (29%), average (61.4%), and excellent (9.7%) HRQOL. None of the latent profiles was associated with autoantibody profiles or diagnostic grouping. Black ethnicity (odds ratio [OR], 0.22; 95% CI, 0.08-0.63), Indo-Asian ethnicity (OR, 0.39; 95% CI, 0.19-0.78), concomitant fibromyalgia (OR, 0.40; 95% CI, 0.20-0.78), sicca symptoms (OR, 0.56; 95% CI, 0.32-0.98), and multimorbidity (Charlson Comorbidity Index; OR, 0.81; 95% CI, 0.67-0.97) were all associated with the “poor” HRQOL latent profile.
Study limitations included the lack of validated scoring systems to measure cross-disease activity in CTDs, the lack of collection of disease-specific disease activity measures; the cross-sectional design; and potentially limited precision because of the small numbers of patients with these diseases.
The study authors concluded, “We identified a number of key demographic, lifestyle and clinical factors associated with poor [HRQOL] in this population. These factors need to be addressed across the whole CTD spectrum as part of a holistic management approach aimed at improving overall patient outcomes.”
Disclosure: Some of the study authors have declared affiliations with biotech, pharmaceutical, and/or device companies. Please see the original reference for a full list of authors’ disclosures.
Dyball S, Reynolds JA, Herrick AL, et al. Determinants of health-related quality of life across the spectrum of connective tissue diseases using latent profile analysis: results from the LEAP cohort. Rheumatology (Oxford). Published online December 19, 2022. doi:10.1093/rheumatology/keac680