ArticleEClinicalMedicine2023
Patterns of patient-reported symptoms and association with sociodemographic and systemic sclerosis disease characteristics: a scleroderma Patient-centered Intervention Network (SPIN) Cohort cross-sectional study.
Article in EClinicalMedicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Understanding patient-reported disease burden in systemic sclerosis: key clinical and demographic features revealed by the EULAR Systemic Sclerosis Impact of Disease (ScleroID) Questionnaire.EULAR rheumatology open · 2026Article
- Clustering characteristics of upper gastrointestinal cancer risk behaviours and their association with social determinants of health: a latent class analysis.Scientific reports · 2026Article
- Symptom clustering of old adult dysphagic patient phenotypes by unsupervised machine learning using multidimensional characteristics: a cross-sectional study.BMC geriatrics · 2026Article
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16 authors.
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Abstract
Background: Systemic sclerosis is a heterogenous disease in which little is known about patterns of patient-reported symptom clusters. We aimed to identify classes of individuals with similar anxiety, depression, fatigue, sleep disturbance, and pain symptoms and to evaluate associated sociodemographic and disease-related characteristics. Methods: This multi-centre cross-sectional study used baseline data from Scleroderma Patient-centered Intervention Network Cohort participants enrolled from 2014 to 2020. Eligible participants completed the PROMIS-29 v2.0 measure. Latent profile analysis was used to identify homogeneous classes of participants based on patterns of anxiety, depression, fatigue, sleep disturbance, and pain scores. Sociodemographic and disease-related characteristics were compared across classes. Findings: Among 2212 participants, we identified five classes, including four classes with "Low" (565 participants, 26%), "Normal" (651 participants, 29%), "High" (569 participants, 26%), or "Very High" (193 participants, 9%) symptom levels across all symptoms. Participants in a fifth class, "High Fatigue/Sleep/Pain and Low Anxiety/Depression" (234 participants, 11%) had similar levels of fatigue, sleep disturbance, and pain as in the "High" class but low anxiety and depression symptoms. There were significant and substantive trends in sociodemographic characteristics (age, education, race or ethnicity, marital or partner status) and increasing disease severity (diffuse disease, tendon friction rubs, joint contractures, gastrointestinal symptoms) across severity-based classes. Disease severity and sociodemographic characteristics of "High Fatigue/Sleep/Pain and Low Anxiety/Depression" class participants were similar to the "High" severity class. Interpretation: Most people with systemic sclerosis can be classified by levels of patient-reported symptoms, which are consistent across symptoms and highly associated with sociodemographic and disease-related variables, except for one group which reports low mental health symptoms despite high levels of other symptoms and substantial disease burden. Studies are needed to better understand resilience in systemic sclerosis and to identify and facilitate implementation of cognitive and behavioural strategies to improve coping and overall quality of life. Funding: National Institute of Nursing Research (F31NR019007), Canadian Institutes of Health Research, Arthritis Society Canada, the Lady Davis Institute for Medical Research, the Jewish General Hospital Foundation, McGill University, Scleroderma Society of Ontario, Scleroderma Canada, Sclérodermie Québec, Scleroderma Manitoba, Scleroderma Atlantic, Scleroderma Association of BC, Scleroderma SASK, Scleroderma Australia, Scleroderma New South Wales, Scleroderma Victoria, and Scleroderma Queensland.
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