Cargando…

Preventing rheumatoid arthritis: Preferences for and predicted uptake of preventive treatments among high risk individuals

OBJECTIVE: To understand preferences for and estimate the likely uptake of preventive treatments currently being evaluated in randomized controlled trials with individuals at increased risk of developing rheumatoid arthritis (RA). METHODS: Focus groups were used to identify key attributes of potenti...

Descripción completa

Detalles Bibliográficos
Autores principales: Harrison, Mark, Spooner, Luke, Bansback, Nick, Milbers, Katherine, Koehn, Cheryl, Shojania, Kam, Finckh, Axel, Hudson, Marie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6483264/
https://www.ncbi.nlm.nih.gov/pubmed/31022252
http://dx.doi.org/10.1371/journal.pone.0216075
Descripción
Sumario:OBJECTIVE: To understand preferences for and estimate the likely uptake of preventive treatments currently being evaluated in randomized controlled trials with individuals at increased risk of developing rheumatoid arthritis (RA). METHODS: Focus groups were used to identify key attributes of potential preventive treatment for RA (reduction in risk of RA, how treatment is taken, chance of side effects, certainty in estimates, health care providers opinion). A web-based discrete choice experiment (DCE) was administered to people at-risk of developing RA, asking them to first choose their preferred of two hypothetical preventive RA treatments, and then between their preferred treatment and ‘no treatment for now.’ DCE data was analyzed using conditional logit regression to estimate the significance and relative importance of attributes in influencing preferences. RESULTS: Two-hundred and eighty-eight first-degree relatives (60% female; 66% aged 18–39 years) completed all tasks in the survey. Fourteen out of fifteen attribute levels significantly influenced preferences for treatments. How treatment is taken (oral vs. infusion β0.983, p<0.001), increasing reduction in risk of RA (β0.922, p<0.001), health care professional preference (β0.900, p<0.001), and avoiding irreversible (β0.839, p<0.001) or reversible serious side effects (β0.799, p<0.001) were most influential. Predicted uptake was high for non-biologic drugs (e.g. 84% hydroxycholoroquine), but very low for atorvastatin (8%) and biologics (<6%). CONCLUSION: Decisions to take preventative treatments are complex, and uptake depends on how treatments can compromise on convenience, potential risks and benefits, and recommendations/preferences of health care professionals. This evidence contributes to understanding whether different preventative treatment strategies are likely to be acceptable to target populations.