A discrete choice experiment methodology allows researchers to better assess the burden of disease on people with rare conditions.
One of the biggest challenges when developing effective treatments for rare diseases is gathering sufficient data to quantify disease impact or gauge responses to treatment. A study by Analysis Group and academic and industry researchers describes a more efficient and flexible method for determining the impacts of diseases or treatments on patients.
Our study of acute myeloid leukemia (AML), a rare blood cancer, was the first to use a discrete choice experiment (DCE) methodology to establish societal preferences directly for disease-specific health states, also known as health state utility values. Utilities represent values linked to well-being, such as disease-related symptoms, energy level, emotional health, or functional status, such as ability to work. A utility value of 0 represents death, and a value of 1 represents perfect health. Values are used to derive quality-adjusted life years (QALYs) to reflect disease status. Taking into account both quality and quantity of years of life, QALYs can influence regulatory, reimbursement, and pricing decisions.
We applied the DCE methodology in an online survey of a representative sample of the general US population. Study participants chose between two alternatives in 12 life scenarios related to AML. (See figure.)
This novel use of the DCE methodology provides greater sensitivity for utility value assessment, particularly for rare diseases, than conventional methods such as EuroQol’s EQ-5D (frequently used for cost-effectiveness models). It allows preference values to be estimated accurately with improved efficiency and greater flexibility than had been possible with other approaches. ■
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