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DiSantostefano RL, Smith IP, Falahee M, Jiménez-Moreno AC, Oliveri S, Veldwijk J, de Wit GA, Janssen EM, Berlin C, Groothuis-Oudshoorn CGM. Research Priorities to Increase Confidence in and Acceptance of Health Preference Research: What Questions Should be Prioritized Now? THE PATIENT 2024; 17:179-190. [PMID: 38103109 PMCID: PMC10894084 DOI: 10.1007/s40271-023-00650-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 10/01/2023] [Indexed: 12/17/2023]
Abstract
BACKGROUND AND OBJECTIVE There has been an increase in the study and use of stated-preference methods to inform medicine development decisions. The objective of this study was to identify prioritized topics and questions relating to health preferences based on the perspective of members of the preference research community. METHODS Preference research stakeholders from industry, academia, consultancy, health technology assessment/regulatory, and patient organizations were recruited using professional networks and preference-targeted e-mail listservs and surveyed about their perspectives on 19 topics and questions for future studies that would increase acceptance of preference methods and their results by decision makers. The online survey consisted of an initial importance prioritization task, a best-worst scaling case 1 instrument, and open-ended questions. Rating counts were used for analysis. The best-worst scaling used a balanced incomplete block design. RESULTS One hundred and one participants responded to the survey invitation with 66 completing the best-worst scaling. The most important research topics related to the synthesis of preferences across studies, transferability across populations or related diseases, and method topics including comparison of methods and non-discrete choice experiment methods. Prioritization differences were found between respondents whose primary affiliation was academia versus other stakeholders. Academic researchers prioritized methodological/less studied topics; other stakeholders prioritized applied research topics relating to consistency of practice. CONCLUSIONS As the field of health preference research grows, there is a need to revisit and communicate previous work on preference selection and study design to ensure that new stakeholders are aware of this work and to update these works where necessary. These findings might encourage discussion and alignment among different stakeholders who might hold different research priorities. Research on the application of previous preference research to new contexts will also help increase the acceptance of health preference information by decision makers.
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Affiliation(s)
| | - Ian P Smith
- Janssen Research & Development LLC, 1125 Trenton Harbourton Rd, Titusville, NJ, 08560, USA
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Marie Falahee
- Rheumatology Research Group, Institute of Inflammation and Ageing, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
| | | | - Serena Oliveri
- Applied Research Division for Cognitive and Psychological Science, Istituto Europeo di Oncologia, IEO IRCCS, Milan, Italy
| | - Jorien Veldwijk
- Erasmus School of Health Policy & Management, Erasmus University Rotterdam, Rotterdam, The Netherlands
- Erasmus Choice Modelling Centre, Erasmus University Rotterdam, Rotterdam, The Netherlands
| | - G Ardine de Wit
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Ellen M Janssen
- Janssen Research & Development LLC, 1125 Trenton Harbourton Rd, Titusville, NJ, 08560, USA
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Veldwijk J, Smith IP, Oliveri S, Petrocchi S, Smith MY, Lanzoni L, Janssens R, Huys I, de Wit GA, Groothuis-Oudshoorn CGM. Comparing Discrete Choice Experiment with Swing Weighting to Estimate Attribute Relative Importance: A Case Study in Lung Cancer Patient Preferences. Med Decis Making 2024; 44:203-216. [PMID: 38178591 PMCID: PMC10865764 DOI: 10.1177/0272989x231222421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 12/06/2023] [Indexed: 01/06/2024]
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.
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Affiliation(s)
- J. Veldwijk
- Erasmus School of Health Policy & Management, Erasmus University, Rotterdam, the Netherlands
- Erasmus Choice Modelling Centre, Erasmus University, Rotterdam, the Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Julius Centrum, Utrecht, the Netherlands
| | - I. P. Smith
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Julius Centrum, Utrecht, the Netherlands
| | - S. Oliveri
- Applied Research Division for Cognitive and Psychological Science, IEO, European Institute of Oncology IRCCS, Milan, Italy
| | - S. Petrocchi
- Applied Research Division for Cognitive and Psychological Science, IEO, European Institute of Oncology IRCCS, Milan, Italy
| | - M. Y. Smith
- Alexion AstraZeneca Rare Disease, Boston, MA, USA
- Department of Regulatory and Quality Sciences, School of Pharmacy, University of Southern California, Los Angeles, CA, USA
| | - L. Lanzoni
- Applied Research Division for Cognitive and Psychological Science, IEO, European Institute of Oncology IRCCS, Milan, Italy
| | - R. Janssens
- Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium
| | - I. Huys
- Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium
| | - G. A. de Wit
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Julius Centrum, Utrecht, the Netherlands
- Department of Health Sciences, Faculty of Science, Vrije Universiteit Amsterdam & Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - C. G. M Groothuis-Oudshoorn
- Health Technology and Services Research (HTSR), Faculty of Behavioural Management and Social Sciences, University of Twente, Enschede, the Netherlands
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DiSantostefano RL, Simons G, Englbrecht M, Humphreys JH, Bruce IN, Bywall KS, Radawski C, Raza K, Falahee M, Veldwijk J. Can the General Public Be a Proxy for an "At-Risk" Group in a Patient Preference Study? A Disease Prevention Example in Rheumatoid Arthritis. Med Decis Making 2024; 44:189-202. [PMID: 38240281 PMCID: PMC10865770 DOI: 10.1177/0272989x231218265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 11/02/2023] [Indexed: 02/15/2024]
Abstract
BACKGROUND When selecting samples for patient preference studies, it may be difficult or impractical to recruit participants who are eligible for a particular treatment decision. However, a general public sample may not be an appropriate proxy. OBJECTIVE This study compares preferences for rheumatoid arthritis (RA) preventive treatments between members of the general public and first-degree relatives (FDRs) of confirmed RA patients to assess whether a sample of the general public can be used as a proxy for FDRs. METHODS Participants were asked to imagine they were experiencing arthralgia and had screening tests indicating a 60% chance of developing RA within 2 yrs. Using a discrete choice experiment, participants were offered a series of choices between no treatment and 2 unlabeled hypothetical treatments to reduce the risk of RA. To assess data quality, time to complete survey sections and comprehension questions were assessed. A random parameter logit model was used to obtain attribute-level estimates, which were used to calculate relative importance, maximum acceptable risk (MAR), and market shares of hypothetical preventive treatments. RESULTS The FDR sample (n = 298) spent more time completing the survey and performed better on comprehension questions compared with the general public sample (n = 982). The relative importance ranking was similar between the general public and FDR participant samples; however, other relative preference measures involving weights including MARs and market share differed between groups, with FDRs having numerically higher MARs. CONCLUSION In the context of RA prevention, the general public (average risk) may be a reasonable proxy for a more at-risk sample (FDRs) for overall relative importance ranking but not weights. The rationale for a proxy sample should be clearly justified. HIGHLIGHTS Participants from the general public were compared to first-degree relatives on their preferences for rheumatoid arthritis (RA) preventive treatments using a discrete choice experiment.Preferences were similar between groups in terms of the most important and least important attributes of preventive treatments, with effectiveness being the most important attribute. However, relative weights differed.Attention to the survey and predicted market shares of hypothetical RA preventive treatments differed between the general public and first-degree relatives.The general public may be a reasonable proxy for an at-risk group for patient preferences ranks but not weights in the disease prevention context; however, care should be taken in sample selection for patient preference studies when choosing nonpatients.
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Affiliation(s)
| | - G. Simons
- Rheumatology Research Group, Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK
| | - M. Englbrecht
- freelance healthcare data scientist, Eckental, Germany
- Department of Internal Medicine and Institute for Clinical Immunology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Jennifer H. Humphreys
- Centre for Epidemiology Versus Arthritis, Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK
- Kellgren Centre for Rheumatology, Manchester University NHS Foundation Trust, Manchester, UK
| | - Ian N. Bruce
- Centre for Epidemiology Versus Arthritis, Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK
- Kellgren Centre for Rheumatology, Manchester University NHS Foundation Trust, Manchester, UK
- NIHR Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | | | - C. Radawski
- Eli Lilly and Company, Indianapolis, IN, USA
| | - K. Raza
- Rheumatology Research Group, Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK
- Department of Rheumatology, Sandwell and West Birmingham NHS Trust, Birmingham, UK
- MRC Versus Arthritis Centre for Musculoskeletal Ageing Research and Research into Inflammatory Arthritis Centre Versus Arthritis, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
| | - M. Falahee
- Rheumatology Research Group, Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK
| | - J. Veldwijk
- School of Health Policy & Management, Erasmus University Rotterdam, Rotterdam, the Netherlands
- Erasmus Choice Modelling Centre, Erasmus University Rotterdam, Rotterdam, the Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands
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