OBJECTIVES: Several agents have recently been approved for relapsed/refractory multiple myeloma (MM). The existing literature on patient and caregiver preferences for MM treatments is limited. With more treatment options available, it is important to understand patient and caregiver preferences. This study aims to quantify these preferences using a discrete-choice experiment (DCE) survey coupled with a best-worst scaling (BWS) exercise to elicit treatment priorities and unmet needs. METHODS: To design the survey, we used a multiphase, mixed-methods approach to identify key treatment attributes and levels. A literature review, focus groups, and consultation with research team members yielded important treatment attributes including effectiveness, toxicity, treatment schedule and burden, travel time to the hospital for treatment, and cost. DCE surveys provide quantitative information on tradeoffs but only accommodate a limited number of attributes. BWS provides a quantitative ranking of importance and can include a larger number of attributes. We designed a survey with both a DCE and a BWS exercise that included attributes that overlapped between the 2 types of patient preference questions to provide multiple sources of information on treatment preferences. RESULTS: The draft DCE and BWS survey were developed and pretested in face-to-face semistructured interviews with patients (n = 31) and caregivers (n = 24). The final DCE includes 6 attributes with varying levels: progression-free survival (PFS, 6-24 months); risk of heart failure (0%-5%); peripheral neuropathy (none, mild-to-moderate, severe); risk of low blood counts, combining thrombocytopenia and neutropenia (0%-70%); gastrointestinal problems (none, nausea and vomiting, diarrhea, constipation), and mode and frequency of administration (daily and weekly pill, weekly injection, intravenous [IV] infusion 4 hours per week, IV 1 hour twice a week). The BWS exercise includes 18 items with some overlap with DCE attribute levels. The study also included a fixed question on treatment cost, offering a choice between 2 hypothetical treatments that cost $200 per month and $600 per month. In the pretests, patients had an average age of 62 years and 68% had income > $59,999. Caregivers had an average age of 57 years and 59% had income > $59,999 (3 patients and 2 caregivers did not provide demographic data). In the DCE, respondents said overall PFS was most important, relative to the other attributes, but their choices of hypothetical treatments indicated a willingness to trade PFS for less treatment toxicity. Caregivers' perceptions of PFS and risk were influenced by the age of the person for whom they were caring. To control for this, a question about the patient's age was added to the caregiver survey. The final survey is currently being administered online to patients and caregivers participating in the Multiple Myeloma Research Foundation CoMMpass study. We anticipate surveying 150 patients and 150 caregivers with results ready for the ASH 2017 Annual Meeting. CONCLUSIONS: Evaluations of patient preferences and priorities are increasingly important in regulatory evaluations, which have become more patient centered. Respondent comments from pretests suggest PFS remains a very important attribute to patients and their caregivers. A rigorous evaluation of treatment preferences can be used for education of the clinical and broader medical community on treatment preferences in a landscape that includes several new therapies.

Disclosures

Mansfield: RTI Health Solutions: Other: I am a full time employee of Research Triangle Institute d/b/a RTI Health Solutions. The research that is the subject of this abstract was performed in the course of my employment, pursuant to a contract between my employer and the study sponsor. My em. Chari: Millennium: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol-Myers Squibb: Consultancy, Other: Research funding (to AC's institution); travel, Research Funding; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Research Funding; Array BioPharma: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Research Funding; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Research Funding; Biotest: Other: Research funding (to AC's institution), Research Funding; Onyx: Research Funding; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Research Funding; Pharmacyclics: Research Funding; Acetylon Pharmaceuticals: Other: Research funding (to AC's institution). Kaufman: Amgen, Novartis: Research Funding; Amgen, Roche, BMS, Seattle Genetics, Sutro Biopharma, Pharmacyclics: Consultancy. Siegel: Merck: Consultancy; Celgene, Takeda, Amgen Inc, Novartis and BMS: Consultancy, Speakers Bureau. Zonder: BMS, Celgene: Research Funding; Takeda, Celgene, BMS, Janssen, Seattle Genetics, Prothena: Consultancy, Honoraria; pharmacyclics: Other: Data Safety Monitoring Committee. Mange: RTI Health Solutions: Other: I am a full time employee of Research Triangle Institute d/b/a RTI Health Solutions. The research that is the subject of this abstract was performed in the course of my employment, pursuant to a contract between my employer and the study sponsor. My em. Dalal: , Takeda Pharmaceuticals International Co: Employment, Equity Ownership. Mikhael: Onyx, Celgene, Sanofi, AbbVie: Research Funding.

Author notes

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Asterisk with author names denotes non-ASH members.

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