Patient preference data provide essential insight into patients’ priorities for treatment. An understanding of how patients trade off benefits, risks, and other attributes of treatment is gaining importance in clinical and regulatory decision making[1,2,3]. While methods such as the discrete-choice experiment (DCE) yield robust preference estimates to support decision making, such studies can be time-consuming, costly, and difficult to conduct in rare diseases because of recruitment challenges. Research teams may need to employ alternative exploratory approaches to elicit preference data; in turn, these data can generate foundational evidence for larger studies. Exploratory preference data are particularly useful to inform internal strategy where data are needed for time-critical decisions and the need for scientific rigor is lower, or to guide early decisions for a treatment in the early stages of drug development when there may be uncertainty about the benefit-risk profile.

Several methods exist to collect patient preference information on the trade-offs patients are willing to make among treatment attributes, including qualitative interviews, focus groups, and surveys[4]. Each method captures aspects of patients’ experiences that complement each other and has benefits and shortcomings. Qualitative research, for instance, provides insight into patients’ experiences and preferences as captured in their own words, and allows the interviewer to follow-up on interesting points that patients raise and understand not just the choice a patient makes but also why they made that choice. Insights from qualitative research with patients may be especially useful in the early stages of product development to discern unmet needs and treatment goals[5]. Rigorously conducted formative qualitative research also lends validity to quantitative preference-elicitation[6]. Quantitative patient preference surveys use quantitative preference-elicitation methods (e.g., DCEs) to collect standardized responses that provide insight into the relative importance patients place on different treatment attributes, and quantify the trade-offs patients are willing to make among treatment attributes [6]. Combining qualitative and quantitative methods can provide additional insights that each method alone will not provide.

In this paper, we present a novel mixed-methods approach to elicit exploratory preference data by employing a short quantitative survey followed by patient focus groups to elicit both qualitative and quantitative data. We describe the methods used and present a case study where the approach was applied to patients with generalized myasthenia gravis (gMG), a rare, chronic, heterogeneous, and unpredictable autoimmune disease characterized by dysfunction and damage at the neuromuscular junction. gMG is a debilitating and potentially life-threatening disease resulting in fluctuating chronic muscle weakness (e.g., eyes, mouth, throat, neck, limbs) and fatigability that worsens with activity and usually improves with rest; symptoms and intensity can vary from day to day and from hour to hour [7]. The therapeutic landscape in MG is changing, with the availability of new targeted treatments in recent years (e.g., eculizumab, ravulizumab, efgartigimod, rozanolixizumab, and zilucoplan) [8, 9]. Research regarding patient preferences for MG treatment features is scarce, and the objective of this study was to generate preliminary insights to help better understand patients’ unmet needs and preferences for the benefits and risks of gMG treatments and to inform product development strategies. The mixed-methods approach was selected to gather quantitative preference data in a setting that allowed qualitative exploration of the reasons behind the patients’ benefit-risk preferences.

In a mixed-methods study designed to collect both qualitative and quantitative patient preference information, researchers need to decide the format of the qualitative data collection (e.g., focus group or individual interview) and the type of preference question to include (e.g., DCE, best-worst scaling, or threshold exercise) [10,11,12]. There are known benefits and challenges with each method of qualitative data collection and with the different types of quantitative preference-elicitation questions[13, 14]. The choice of methods should be based on the information needs, timeline, and characteristics of the target population (e.g., prevalence of the condition, disease symptoms that might make focus groups difficult). If the goal is to generate preliminary data on a short timeline, a focused research question is essential. In addition, the use of existing materials to create the preference questions will expedite the process (e.g., past studies, descriptions of attributes created for other reasons). In this study, we present an example from a recently conducted study, designed for efficiency and with a condensed timeline (approximately 4 months), and outline the choices of methods made for this example.