Search

Abstract Background In patients with axial spondyloarthritis (axSpA) or psoriatic arthritis (PsA), concomitant depression might have a negative impact on the course of disease and treatment outcomes. The aims of this analysis are to determine the prevalence of depressive symptoms in axSpA and PsA patients in a real-world cohort study and to identify sociodemographic and clinical associated factors for moderate or severe depressive symptoms in both diseases. Methods Patients from the RABBIT-SpA cohort with an axSpA or PsA diagnosis and a valid WHO-5 Well-Being Index score at baseline were included. A descriptive analysis of baseline and outcome parameters by category of depressive symptoms was performed and factors associated with the presence of depressive symptoms (moderate or severe) were examined in a logistic regression. Results Two thousand four hundred seventy patients (1,245 axSpA; 1,225 PsA) were included in the analysis. In both diagnoses, the proportion of patients with moderate depressive symptoms was 8% and 21% with severe symptoms. Patients with moderate or severe depressive symptoms were less likely to engage in sports than those with no or mild depressive symptoms, had more comorbidities and higher scores for disease activity, functional limitations, fatigue, and pain and took more analgesics. In axSpA, patients with a higher disease activity, a greater functional impairment and more severe fatigue were more likely to experience depressive symptoms, while patients with more years in education and engaging in sports for at least 1 h/week were less likely to experience depressive symptoms. PsA patients with a greater functional impairment and more severe fatigue were more likely to experience depressive symptoms while those engaging in sports for at least 1 h/week were less likely to experience depressive symptoms. Conclusion We confirmed a high prevalence of depressive symptoms in both PsA and axSpA. Factors negatively associated with the presence of depressive symptoms were fatigue, not engaging in sports, and greater functional limitations. Depressive symptoms may affect the perception of disease activity / severity by patients. Thus, depressive symptoms are an important condition in axSpA and PsA that should be considered when evaluating disease activity and treatment outcomes.

Abstract Background Clinical data collection requires correct and complete data sets in order to perform correct statistical analysis and draw valid conclusions. While in randomized clinical trials much effort concentrates on data monitoring, this is rarely the case in observational studies- due to high numbers of cases and often-restricted resources. We have developed a valid and cost-effective monitoring tool, which can substantially contribute to an increased data quality in observational research. Methods An automated digital monitoring system for cohort studies developed by the German Rheumatism Research Centre (DRFZ) was tested within the disease register RABBIT-SpA, a longitudinal observational study including patients with axial spondyloarthritis and psoriatic arthritis. Physicians and patients complete electronic case report forms (eCRF) twice a year for up to 10 years. Automatic plausibility checks were implemented to verify all data after entry into the eCRF. To identify conflicts that cannot be found by this approach, all possible conflicts were compiled into a catalog. This “conflict catalog” was used to create queries, which are displayed as part of the eCRF. The proportion of queried eCRFs and responses were analyzed by descriptive methods. For the analysis of responses, the type of conflict was assigned to either a single conflict only (affecting individual items) or a conflict that required the entire eCRF to be queried. Results Data from 1883 patients was analyzed. A total of n = 3145 eCRFs submitted between baseline (T0) and T3 (12 months) had conflicts (40–64%). Fifty-six to 100% of the queries regarding eCRFs that were completely missing were answered. A mean of 1.4 to 2.4 single conflicts occurred per eCRF, of which 59–69% were answered. The most common missing values were CRP, ESR, Schober’s test, data on systemic glucocorticoid therapy, and presence of enthesitis. Conclusion Providing high data quality in large observational cohort studies is a major challenge, which requires careful monitoring. An automated monitoring process was successfully implemented and well accepted by the study centers. Two thirds of the queries were answered with new data. While conventional manual monitoring is resource-intensive and may itself create new sources of errors, automated processes are a convenient way to augment data quality.