OBJECTIVES: Hemophilia is a rare bleeding disorder which requires a complex diagnosis and management. The objective of this study was to assess patient preferences for alternative treatments, treatment-related benefits and risks in the therapy of hemophilia A.

METHODS:A literature search and pre-test interviews were conducted to determine the most relevant attributes in terms of effects, risks, and administration of a hemophilia A treatment. A Best-Worst Scaling (BWS) Case 3 approach with four attributes was applied: bleeding frequency per year, type of application, risk of thromboembolic events, development of inhibitors. The BWS was conducted between October 2018 and May 2019 using a fractional factorial design. Each respondent answered 13 choice tasks, including one dominant task, comparing three different treatment profiles. Data was analyzed using random-parameters logit models.

RESULTS: The preliminary analysis included N=49 patients (98.0% male). “Bleeding frequency per year” (Level Difference (LD): 7.833) and “development of inhibitors” (LD: 6.369) had the greatest impact on respondents’ decisions. Patients disliked being at risk of inhibitor development more than being at risk of thromboembolic events (LD: 2.399). The type of application, either intravenous or subcutaneous, was of less importance (LD: 1.405). There was a significant preference variation for all attributes. All coefficients proved to be significantly different from zero at the level p≤0.01.

CONCLUSIONS: This study identifies and weights key decision-making criteria for optimal management of hemophilia A from the perspective of patients. Patients value low frequency of bleeding per year and low risk of development of inhibitors higher than remaining attribute levels in the decision context of the study. An increase of risk and frequency would significantly decrease the impact on choice decisions. The application does not seem to influence the choice decision very much compared to the other attributes. Regarding preference heterogeneity, further analysis is needed to identify subgroups among patients and their characteristics.