Assessing Patient Preferences in Rare Diseases: Direct Preference Elicitation in the Rare Chronic Kidney Disease, Immunoglobulin A Nephropathy

Kevin Marsh (), Kerrie-Anne Ho, Rachel Lo, Nancy Zaour, Aneesh Thomas George and Nigel S. Cook
Additional contact information
Kevin Marsh: Evidera
Kerrie-Anne Ho: UCB Pharma
Rachel Lo: Evidera
Nancy Zaour: Novartis Pharma AG
Aneesh Thomas George: Novartis Healthcare Pvt. Ltd
Nigel S. Cook: Novartis Pharma AG

The Patient: Patient-Centered Outcomes Research, 2021, vol. 14, issue 6, No 12, 837-847

Abstract: Abstract Background Patient preference information is increasingly being used to inform decision making; however, further work is required to support the collection of preference information in rare diseases. This study illustrates the use of direct preference elicitation methods to collect preference data from small samples in the context of early decision making to inform the development of a product for the treatment of immunoglobulin A nephropathy. Method An interview-based swing weighting approach was used to elicit preferences from 40 patients in the US and China. Attributes were identified through a background review, expert engagement and patient focus groups. Participants completed a series of tasks that involved ranking, rating and scoring improvements in the attributes to obtain attribute swing weights and partial value functions. The preference results were then incorporated into a benefit-risk assessment simulation tool. Results Participants placed the greatest value on avoiding end-stage renal/kidney disease. Similar weight was given to short-term quality-of-life improvements and avoiding infections. Treatment burden (number of vaccinations) received the least weight. Heterogeneity in preferences was also observed. Consistency tests did not identify statistically significant variation in preferences, and qualitative data suggested that the elicitation exercise was sensitive to participants’ interpretation of attributes and that participants were able to express their preferences. Conclusion Direct preference elicitation methods can be used to collect preference data from small samples. Further work should continue to test the validity of the estimate generated by such methods.

Date: 2021
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DOI: 10.1007/s40271-021-00521-3

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