Individual Trade-Offs Between Possible Benefits and Risks of Cancer Treatments: Results from a Stated Preference Study with Patients with Multiple Myeloma

Abstract

Background: The objectives of this study were to elicit the preferences of patients with multiple myeloma regarding the possible benefits and risks of cancer treatments and to illustrate how such data may be used to estimate patients' acceptance of new treatments.

Patients and methods: Patients with multiple myeloma from the cancer charity Myeloma UK were invited to participate in an online survey based on multicriteria decision analysis and swing weighting to elicit individual stated preferences for the following attributes: (a) 1-year progression-free survival (PFS, ranging from 50% to 90%), (b) mild or moderate toxicity for 2 months or longer (ranging from 85% to 45%), and (c) severe or life-threatening toxicity (ranging from 80% to 20%).

Results: A total of 560 participants completed the survey. The average weight given to PFS was 0.54, followed by 0.32 for severe or life-threatening toxicity and 0.14 for mild or moderate chronic toxicity. Participants who ranked severe or life-threatening toxicity above mild or moderate chronic toxicity (56%) were more frequently younger, working, and looking after dependent family members and had more frequently experienced severe or life-threatening side effects. The amount of weight given to PFS did not depend on any of the collected covariates. The feasibility of using the collected preference data to estimate the patients' acceptance of specific multiple myeloma treatments was demonstrated in a subsequent decision analysis example.

Conclusion: Stated preference studies provide a systematic approach to gain knowledge about the distribution of preferences in the population and about what this implies for patients' acceptance of specific treatments.

Implications for practice: This study demonstrated how quantitative preference statements from a large group of participants can be collected through an online survey and how such information may be used to explore the acceptability of specific treatments based on the attributes studied. Results from such studies have the potential to become an important new tool for gathering patient views and studying heterogeneity in preferences in a systematic way, along with other methods, such as focus groups and expert opinions.

Keywords: Benefit‐risk assessment; Multicriteria decision analysis; Patient preferences; Regulatory science.

Figure 1.

Schematic representation of the steps taken in this study. In step 1 (Design), a model is set up with the help of a focus group, with attributes of interest and ranges on which preferences will be collected. In step 2 (Elicit), a questionnaire is used first to elicit the ordinal ranking of the attributes considering the full range of alternatives; then choice matching is used to elicit trade‐offs by comparing different levels for pairwise attributes, and the process is repeated for all attributes. In step 3 (Analyze), the data collected in the survey are transformed into a set of weights reflecting the relative importance of the considered attributes. In Step 4 (Apply), the elicited preferences are combined with data from a clinical trial to assess acceptability of two treatments based on the individual elicited weights. Abbreviations: G1–2, mild or moderate toxicity; G3–4, severe or life‐threatening toxicity; PFS, progression‐free survival.

Figure 2.

Part worth associated with the different levels for each attribute. The red points represent the average (mean) part worth at each attribute level.

Figure 3.

Ternary plot showing the joint distribution of the attribute weights. The left axis displays the weight given to mild or moderate chronic toxicity, the right axis displays the weight given to PFS, and the bottom axis displays the weight given to severe or life‐threatening toxicity. The black points represent the attribute weights of the individual study participants, and the red diamond represents the average weight given to the three attributes (0.54 for PFS, 0.32 for severe or life‐threatening toxicity, and 0.14 for mild or moderate chronic toxicity). The colored polygons represent areas with a different ordinal ranking of the attribute weights. Abbreviations: mod, moderate chronic toxicity; PFS, progression‐free survival; sev, severe toxicity.