705 - Patient preferences for atopic dermatitis treatment profiles: results from a discrete choice experiment
Authors: Matthew Quaife, Sarah Mulnick, Harrison Clarke, Kerry Noonan, Gaelle Le-Bagousse-Bego, Debra Sierka, El-Bdaoui Haddad, Raj Chovatiya
Journal: British Journal of Dermatology (2024)

Abstract Introduction Although atopic dermatitis (AD) primarily affects the skin, it is increasingly recognized as a systemic inflammatory disease associated with immense patient burden and heterogenous impact on quality of life with significant implications for management and treatment. The AD treatment landscape is rapidly evolving with developments in biologic and non-biologic treatments, and it is therefore important to understand how patients make decisions between treatment benefits, administration, and risks. Objectives To quantify the impact of AD treatment attributes on patient preferences. Methods 400 adults with AD in the United States completed an online discrete choice experiment (DCE) survey between November 2023 and January 2024. DCE attributes and levels were selected based on a targeted literature review of evidence of approved AD treatments. In each task, patients chose between two hypothetical treatment profiles or opted to continue with their current treatment. The treatments were described by the chance of achieving clearer skin, achieving itch reduction, time to onset of action, risk of experiencing a side effect leading to treatment discontinuation, risk of injection site reaction, presence of FDA boxed warning, and type and frequency of administration. Patients also completed sociodemographic, quality of life, and clinical questionnaires and the Atopic Dermatitis Control Tool (ADCT). Preference data were analyzed using an effects-coded mixed-multinomial-logit model (MXL) and latent class logit model to identify if different preference patterns coexisted in the sample. Relative attribute importance (RAI) scores were calculated and patient willingness to trade-off between attributes was assessed. Results Mean age was 44.9 years (range: 18–83), 72% were female, 78% white, and 10% were Hispanic/Latino. Topical treatments were currently used by 78%, whilst 42% used oral, and 13% injectable. One-third (34%) had experience (currently or previously) using a medication with an FDA boxed warning. Patients had a mean ADCT score of 6.95, where ≥7 indicates poorly controlled AD. Three groups of patients with distinct preference patterns were identified: Boxed Warning Avoiders (BWA; 11.5%), Injectable Avoiders (IA; 23.1%) and Efficacy Focused (EF; 65.4%). Across all groups, increasing AD treatment benefits (achieving clearer skin RAI: 28%; reducing itch: 22%) had the greatest influence on treatment preference vs. avoiding risks (discontinuation: 9%; FDA warning: 9%; injection site reaction: 9%). However, the relative importance of attributes varied. Boxed Warning Avoiders were strongly averse to the FDA boxed warning and placed a higher importance on itch reduction and avoiding treatment discontinuation. Injectable Avoiders placed the highest importance on mode and frequency of administration, preferring oral or topical treatment vs. injection regardless of frequency; they also prioritized avoiding the risk of injection site reaction. Efficacy Focused prioritized itch reduction and clearer skin nearly twice as much as other groups, and placed less value on differentiating aspects of treatments including type and frequency of administration. Conclusions Overall, patients with AD valued clinical benefits and lower risks. Heterogeneity observed within the preferences demonstrated that while all groups valued efficacy, the extent to which they were willing to accept different modes of administration and levels of risk varied. This study offers insight into the value patients place on AD treatment attributes, and reflects the need for education to understand the factors that could contribute to selecting the appropriate treatment and to support shared decision-making between patients and their healthcare professionals.