OBJECTIVES: Medical advances have allowed research and innovation in interventions of rare diseases to grow exponentially in the past few decades. However, clinical evidence in rare disease is often associated with high levels of uncertainty due to small patient numbers and heterogeneity of conditions. Stated preference data can provide supporting evidence during the development, regulatory approval and marketing of rare disease interventions in situations where decision-making may be preference-sensitive, for example, when considerable clinical uncertainty exists or where multiple viable treatments are available. The objective of this review was to identify and describe stated preference methods used to understand stakeholder preferences in rare disease and any associated challenges.

METHODS: A systematic search of six electronic databases combining terms relating to “stated preference” and “rare disease” was conducted in April 2023. Narrative synthesis was used to summarize findings based on data extraction conducted by two independent researchers covering disease area, intervention type, study population, design features, analysis and outcomes. The quality of studies was assessed using the PREFS checklist.

RESULTS: In total, 42 studies were identified for inclusion. Studies used a range of methods including discrete choice experiments (DCEs) (55%), best-worst scaling (19%) and multi-criteria decision analysis (10%). Studies were conducted in over 20 rare diseases, most commonly hemophilia A (29%). Interventions included treatments (83%), diagnostic testing (10%), screening (5%) and preventative care (2%). Preferences were derived from patients (50%), caregivers (52%), medical experts (17%), and general population (19%) with sample sizes ranging between 5 and 2382. The robustness and interpretation of findings often appeared limited by small sample sizes, particularly in DCEs.

CONCLUSIONS: DCEs remain the leading stated preference method in rare disease despite challenges in participant recruitment leading to potentially underpowered studies. Alternative methods requiring smaller sample sizes should be considered for addressing stated preference research questions in rare disease.