Session Type: Poster Session (Sunday)
Session Time: 9:00AM-11:00AM
Background/Purpose: Pain is one of the most pressing problems for Rheumatoid Arthritis (RA) patients and contributes substantially towards fatigue and disability. Experiences of pain in real world settings may be captured through the use of innovative mobile apps. This study investigates the relationship between pain and patient demographics, clinical features, and health outcomes in a cohort of RA patients recruited via a mobile app.
Methods: A novel mobile app, funded by GSK, known as the PARADE app (PAtient Rheumatoid Arthritis Data from the rEal world) was developed using Apple ResearchKit™ software in 2016. This app obtained informed consent and captured patient demographics, comorbidities, medication use, and PRO instruments – i.e. the Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F) and Health Assessment Questionnaire – Disability Index (HAQ-DI). Participants self-reported as being diagnosed with RA and being 18 years or older. A cross-sectional design with week 1 data was used, and Pearson correlations calculated. Pain was measured on a 0 to 10 scale and grouped into: low (0-2), mild (3-5), moderate (6-8) and severe (9-10) pain.
Results: Pain scores were recorded for 421 RA patients; 28.5% of with low pain, 39.0% with mild, 23.3% with moderate, and 9.3% with severe pain, regardless of medication use. Most patients were female (79.1%) and Caucasian (80.5%), however 28.2% of the severe pain group were Hispanic (vs only 9.3% of the low-to-moderate pain group).
Pain score was correlated with tender joint count (correlation r 0.30, p < .0001) and degree of morning stiffness (r 0.41, p < .0001). The most bothersome RA symptom was joint pain (ranging from 74.2% to 94.9% across pain groups), followed by fatigue (60.8% to 79.3%). Pain was highly correlated with FACIT-F and HAQ-DI scores (r 0.38 and 0.54 respectively, both p < .0001). Pain was also correlated with each HAQ-DI subcategory (all p < .0001).
Osteoarthritis (OA) was more common in those with moderate pain (34.7%), than low or severe pain (14.2% and 23.1%, respectively). Fibromyalgia was most common in moderate pain patients (36.7%), but less frequent in low and severe pain patients (3.3% and 20.5% respectively). Mood was not associated with pain, and while depression was present in 34.7% of moderate pain patients, it was less common in severe (23.1%) or low (16.7%) pain patients.
Pain medication was frequently used by those with moderate pain (85.7%), but lower levels of use were reported in low (55.0%) or severe (66.7%) pain patients. Conventional Disease-Modifying Anti-Rheumatic Drug (cDMARD) use was common in both low-to-moderate pain groups (61.0% to 68.3%), but only 35.9% in the severe pain subgroup. Biologic DMARDS (bDMARDs) were used by 49.0% of moderate pain patients, but only by 35.9% of severe pain patients.
Conclusion: Pain remains an area of high unmet need in this RA patient cohort. Pain was highly associated with measures of fatigue and disability. However, comorbidities such as OA, fibromyalgia, and depression may be more common in patients with moderate pain than severe or low pain. Patients with severe pain reported lower levels of cDMARD and bDMARD treatment, indicating possible undertreatment of pain in this group.
To cite this abstract in AMA style:Dickinson H, Liu Y, Williams R. The Relationship Between Pain and Patient Demographics, Clinical Features, and Health Outcomes in a Cohort of Rheumatoid Arthritis Patients Recruited and Studied Using a Mobile Application [abstract]. Arthritis Rheumatol. 2019; 71 (suppl 10). https://acrabstracts.org/abstract/the-relationship-between-pain-and-patient-demographics-clinical-features-and-health-outcomes-in-a-cohort-of-rheumatoid-arthritis-patients-recruited-and-studied-using-a-mobile-application/. Accessed June 5, 2020.
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ACR Meeting Abstracts - https://acrabstracts.org/abstract/the-relationship-between-pain-and-patient-demographics-clinical-features-and-health-outcomes-in-a-cohort-of-rheumatoid-arthritis-patients-recruited-and-studied-using-a-mobile-application/