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Implementing an automated monitoring process in a digital, longitudinal observational cohort study
(2021)
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.
Introduction: Improvements in both musculoskeletal and non-musculoskeletal manifestations are important treatment goals in psoriatic arthritis (PsA). Objective: These post hoc analyses determined whether additional benefits related to various PsA domains are observed in patients simultaneously achieving 50% improvement in American College of Rheumatology criteria (ACR50) and 100% improvement in Psoriasis Area Severity Index (PASI100), the primary endpoint of the SPIRIT-H2H study. Methods: Patients with active PsA and psoriasis in SPIRIT-H2H (N = 566) were categorised into two sets of four response groups irrespective of treatment allocation (approved dosages of ixekizumab or adalimumab): patients who simultaneously achieved ACR50 and PASI100 response, achieved ACR50 response only, achieved PASI100 response only, or did not achieve ACR50 or PASI100 response after 24 and 52 weeks of treatment. Patients achieving simultaneous ACR50 and PASI100 response were compared with the other patient response groups at the corresponding time point for efficacy and health-related quality of life (HRQoL) outcomes. Results: Patients simultaneously achieving ACR50 and PASI100 responses at week 24 or 52 showed higher rates of ACR70 response, minimal disease activity, Disease Activity in Psoriatic Arthritis ≤ 4, resolution of enthesitis and dactylitis, and HRQoL improvement at weeks 24 and 52, respectively, than the other corresponding response groups at both time points. Conclusion: High levels of disease control, such as those obtained with simultaneous achievement of ACR50 and PASI100 response, were linked to better outcomes across a wide range of endpoints that are important for patients with PsA. Patients meeting this combined endpoint showed more comprehensive and thus greater control of disease activity.
Correction to: Clinical Rheumatology. DOI: https://doi.org/10.1007/s10067-021-05891-5
In the original published version of this article, the Figure 4 contained error. The line “ACR50 plus PASI100” has been presented incorrectly. The Figure 4 is now presented correctly. The original article has been corrected.