Abstract
INTRODUCTION: Discrete choice experiments (DCE) are commonly used to elicit patient preferences and to determine the relative importance of attributes but can be complex and costly to administer. Simpler methods that measure relative importance exist, such as swing weighting with direct rating (SW-DR), but there is little empirical evidence comparing the two. This study aimed to directly compare attribute relative importance rankings and weights elicited using a DCE and SW-DR.
METHODS: A total of 307 patients with non-small-cell lung cancer in Italy and Belgium completed an online survey assessing preferences for cancer treatment using DCE and SW-DR. The relative importance of the attributes was determined using a random parameter logit model for the DCE and rank order centroid method (ROC) for SW-DR. Differences in relative importance ranking and weights between the methods were assessed using Cohen's weighted kappa and Dirichlet regression. Feedback on ease of understanding and answering the 2 tasks was also collected.
RESULTS: Most respondents (>65%) found both tasks (very) easy to understand and answer. The same attribute, survival, was ranked most important irrespective of the methods applied. The overall ranking of the attributes on an aggregate level differed significantly between DCE and SW-ROC ( P < 0.01). Greater differences in attribute weights between attributes were reported in DCE compared with SW-DR ( P < 0.01). Agreement between the individual-level attribute ranking across methods was moderate (weighted Kappa 0.53-0.55).
CONCLUSION: Significant differences in attribute importance between DCE and SW-DR were found. Respondents reported both methods being relatively easy to understand and answer. Further studies confirming these findings are warranted. Such studies will help to provide accurate guidance for methods selection when studying relative attribute importance across a wide array of preference-relevant decisions.
HIGHLIGHTS: Both DCEs and SW tasks can be used to determine attribute relative importance rankings and weights; however, little evidence exists empirically comparing these methods in terms of outcomes or respondent usability.Most respondents found the DCE and SW tasks very easy or easy to understand and answer.A direct comparison of DCE and SW found significant differences in attribute importance rankings and weights as well as a greater spread in the DCE-derived attribute relative importance weights.
Original language | English |
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Pages (from-to) | 272989X231222421 |
Journal | Medical Decision Making |
Volume | 44 |
Issue number | 2 |
DOIs | |
Publication status | E-pub ahead of print - 4 Jan 2024 |
Funding
The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: J. Veldwijk, I. P. Smith, S. Oliveri, S. Petrocchi, L. Lanzoni, Isabelle Huys, Rosanne Janssens, Ardine de Wit, and C. G. M. Groothuis-Oudshoorn declare no conflict of interest. M. Y. Smith is a full-time employee of Alexion AstraZeneca Rare Disease and is a shareholder in the company. The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study formed part of the PREFER project. The Patient Preferences in Benefit-Risk Assessments during the Drug Life Cycle (PREFER) project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No. 115966. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation program and EFPIA. The PREFER project aims to strengthen patient-centric decision-making through evidence-based recommendations guiding stakeholders on how and when patient preference studies should inform medical product development and evaluation. Financial support for this study was provided entirely by a grant from Innovative Medicines Initiative 2 Joint Undertaking under grant No. 11966. The funding agreement ensured the authors’ independence in designing the study, interpreting the data, writing, and publishing the report.
Funders | Funder number |
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Horizon 2020 Framework Programme | |
European Federation of Pharmaceutical Industries and Associations | 11966 |
Innovative Medicines Initiative | 115966 |