S1041 Treatment Patterns of an Adalimumab Biosimilar (ABP 501) Among Patients With Inflammatory Bowel Disease: An Observational Study Using German Pharmacy Claims Database

Abstract

The WPAI-UC is a self-administered six-item survey that generates four metrics: absenteeism (work time missed), presenteeism (impairment whilst working), productivity loss (overall work impairment from the combination of absenteeism and presenteeism), and activity impairment (non-work activity impairment). WPAI component scores are expressed as percentages, with a higher percentage indicating greater impairment and less productivity The IBDQ evaluates disease-related quality of life by 32 items over four domains: bowel (total domain score ranges from 10 to 70), emotional (total domain score ranges from 12 to 84), social (total domain score ranges from 5 to 35), and systemic (total domain score ranges from 5 to 35). For the total score (ranges from 32 to 224) and each domain, a higher score indicates a better quality of life CI,

Treatment Persistence and Switching Patterns of Adalimumab Biosimilar ABP 501 in European Patients with Rheumatologic Diseases

“…Diagnoses were not documented directly in the IQVIA LRx pharmacy claims database and were imputed in German LRx using machine learning models developed based on treatment histories of patients and validated in electronic medical records (Supplemental Information 1) and in French LRx using a mix of rule-based and machine learning approaches (Supplemental Information 2). Those diagnostic algorithms have been successfully applied to previously published studies using the LRx data [16,[18][19][20][21].…”

“…The patient diagnoses were imputed based on models trained using patient treatment history and electronic medical records, which may result in misclassification of disease types. However, the imputation model has been well validated and applied in previously published studies using the German and French LRx databases [16,[18][19][20][21]. Even though there may be a chance to misclassify patients between PsA and RA or AS, the model accuracy to predict the three rheumatologic diseases together can reach 95%.…”