Comparing Discrete Choice Experiment with Swing Weighting to Estimate Attribute Relative Importance: A Case Study in Lung Cancer Patient Preferences

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.

Quantitative Benefit-Risk Assessment in Medical Product Decision Making: A Good Practices Report of an ISPOR Task Force

Benefit-risk assessment is commonly conducted by drug and medical device developers and regulators, to evaluate and communicate issues around benefit-risk balance of medical products. Quantitative benefit-risk assessment (qBRA) is a set of techniques that incorporate explicit outcome weighting within a formal analysis to evaluate the benefit-risk balance. This report describes emerging good practices for the 5 main steps of developing qBRAs based on the multicriteria decision analysis process. First, research question formulation needs to identify the needs of decision makers and requirements for preference data and specify the role of external experts. Second, the formal analysis model should be developed by selecting benefit and safety endpoints while eliminating double counting and considering attribute value dependence. Third, preference elicitation method needs to be chosen, attributes framed appropriately within the elicitation instrument, and quality of the data should be evaluated. Fourth, analysis may need to normalize the preference weights, base-case and sensitivity analyses should be conducted, and the effect of preference heterogeneity analyzed. Finally, results should be communicated efficiently to decision makers and other stakeholders. In addition to detailed recommendations, we provide a checklist for reporting qBRAs developed through a Delphi process conducted with 34 experts.

What matters most to patients with multiple myeloma? A Pan-European patient preference study

INTRODUCTION

Given the rapid increase in novel treatments for patients with multiple myeloma (MM), this patient preference study aimed to establish which treatment attributes matter most to MM patients and evaluate discrete choice experiment (DCE) and swing weighting (SW) as two elicitation methods for quantifying patients' preferences.

METHODS

A survey incorporating DCE and SW was disseminated among European MM patients. The survey included attributes and levels informed by a previous qualitative study with 24 MM patients. Latent class and mixed logit models were used to estimate the DCE attribute weights and descriptive analyses were performed to derive SW weights. MM patients and patient organisations provided extensive feedback during survey development.

RESULTS

393 MM patients across 21 countries completed the survey (M years since diagnosis=6; M previous therapies=3). Significant differences (p<.01) between participants' attribute weights were revealed depending on participants' prior therapy experience, and their experience with side-effects and symptoms. Multivariate analyses showed that participants across the three MM patient classes identified via the latent class model differed regarding their past number of therapies (F=4.772, p=.009). Patients with the most treatments (class 1) and those with the least treatments (class 3) attached more value to life expectancy versus quality of life-related attributes such as pain, mobility and thinking problems. Conversely, patients with intermediary treatment experience (class 2) attached more value to quality of life-related attributes versus life expectancy. Participants highlighted the difficulty of trading-off between life expectancy and quality of life and between physical and mental health. Participants expressed a need for greater psychological support to cope with their symptoms, treatment side-effects, and uncertainties. With respect to patients' preferences for the DCE or SW questions, 42% had no preference, 32% preferred DCE, and 25% preferred SW.

CONCLUSIONS

Quality of life-related attributes affecting MM patients' physical, mental and psychological health such as pain, mobility and thinking problems were considered very important to MM patients, next to life expectancy. This underscores a need to include such attributes in decision-making by healthcare stakeholders involved in MM drug development, evidence generation, evaluation, and clinical practice. This study highlights DCE as the preferred methodology for understanding relative attribute weights from a patient's perspective.

Patient Preferences for Lung Cancer Treatments: A Study Protocol for a Preference Survey Using Discrete Choice Experiment and Swing Weighting

Background: Advanced treatment options for non-small cell lung cancer (NSCLC) consist of immunotherapy, chemotherapy, or a combination of both. Decisions surrounding NSCLC can be considered as preference-sensitive because multiple treatments exist that vary in terms of mode of administration, treatment schedules, and benefit–risk profiles. As part of the IMI PREFER project, we developed a protocol for an online preference survey for NSCLC patients exploring differences in preferences according to patient characteristics (preference heterogeneity). Moreover, this study will evaluate and compare the use of two different preference elicitation methods, the discrete choice experiment (DCE) and the swing weighting (SW) task. Finally, the study explores how demographic (i.e., age, gender, and educational level) and clinical (i.e., cancer stage and line of treatment) information, health literacy, health locus of control, and quality of life may influence or explain patient preferences and the usefulness of a digital interactive tool in providing information on preference elicitation tasks according to patients.

Methods: An online survey will be implemented with the aim to recruit 510 NSCLC patients in Belgium and Italy. Participants will be randomized 50:50 to first receive either the DCE or the SW. The survey will also collect information on participants' disease-related status, health locus of control, health literacy, quality of life, and perception of the educational tool.

Discussion: This protocol outlines methodological and practical steps to quantitatively elicit and study patient preferences for NSCLC treatment alternatives. Results from this study will increase the understanding of which treatment aspects are most valued by NSCLC patients to inform decision-making in drug development, regulatory approval, and reimbursement. Methodologically, the comparison between the DCE and the SW task will be valuable to gain information on how these preference methods perform against each other in eliciting patient preferences. Overall, this protocol may assist researchers, drug developers, and decision-makers in designing quantitative patient preferences into decision-making along the medical product life cycle.

Opportunities and Challenges of Web-Based and Remotely Administered Surveys for Patient Preference Studies in a Vulnerable Population

The application of web-based and remotely administered surveys is becoming increasingly popular due to the fact that it offers numerous advantages over traditional paper-based or computer-based surveys completed in the presence of the researcher. However, it is unclear whether complex preference elicitation tasks administered online in highly vulnerable patient populations are also feasible. This commentary discusses opportunities and challenges of conducting quantitative patient preference studies in lung cancer patients using web-based modes of data collection. We refer to our recent experience in the context of the Patient Preference in Benefit-Risk Assessments during the Drug Life Cycle (PREFER) project. Among the main advantages were the possibility of reaching a wider and geographically distant population in a shorter timeframe while reducing the financial costs of testing, the greater flexibility offered and the reduced burden on the patients. Some limitations were also identified and should be the object of further research, including the potential lack of inclusiveness of the research, the lack of control over who is completing the survey, a poor comprehension of the study material, and ultimately a lower level of engagement with the study. Despite these limitations, experience from the PREFER project suggests that online quantitative methods for data collection may provide a valuable method to explore preferences in vulnerable patient populations beyond the COVID-19 pandemic.