OBJECTIVE: Drug survival is an important proxy measure for effectiveness of treatments for inflammatory diseases such as rheumatoid arthritis (RA), axial spondyloarthritis (AxSpA), psoriatic arthritis (PsA), and psoriasis. The objective of this study was to examine the real-life drug survival of biologics and novel small-molecule therapies across various disease entities such as RA, AxSpA, PsA, and psoriasis.
METHODS: We performed a nationwide cohort study using the prospective nationwide registries DANBIO and DERMBIO, comprising all patients treated with biologics or novel small-molecule therapies for RA, AxSpA, PsA, and psoriasis between January 2015 through May 2021 (DANBIO) and November 2009 to November 2019 (DERMBIO). Drug survival was visualized using Kaplan-Meier curves, and Cox proportional hazards models were used to calculate adjusted Hazard Ratios (HRs) with 95% confidence intervals (CIs) for risk of discontinuing therapy.
FINDINGS: The study comprised a total of 12,089 patients (17,903 treatment series), including 5,104 RA patients (7,867 series), 2,157 AxSpA patients (3,016 series3), 2,551 PsA patients (3,313 series), and 2,577 psoriasis patients (3,707 series). In confounder-adjusted models drug survival in RA was highest for rituximab followed by baricitinib, etanercept and tocilizumab respectively. For AxSpA, drug survival was high for golimumab compared to all other drugs, followed by secukinumab and etanercept and lowest for infliximab. For PsA, tofacitinib and infliximab had the lowest drug survival compared to all other drugs. All other drugs performed almost equally well with a tendency of a somewhat higher drug survival for golimumab, followed by secukinumab and ixekizumab. For psoriasis, drug survival was generally highest for guselkumab.
INTERPRETATION: Differing treatment responses to drugs with various modes of action across RA, AxSpA, PsA and psoriasis emphasize that although these diseases have many overlaps in their pathogenesis, there is a need for an individualized treatment approach that considers the underlying disease, patient profile, and treatment history.