Discrete choice experiment versus swing-weighting:A head-to-head comparison of diabetic patient preferences for glucose-monitoring devices

Introduction Limited evidence exists for how patient preference elicitation methods compare directly. This study compares a discrete choice experiment (DCE) and swing-weighting (SW) by eliciting preferences for glucose-monitoring devices in a population of diabetes patients. Methods A sample of Dutch adults with type 1 or 2 diabetes (n = 459) completed an online survey assessing their preferences for glucose-monitoring devices, consisting of both a DCE and a SW exercise. Half the sample completed the DCE first; the other half completed the SW first. For the DCE, the relative importance of the attributes of the devices was determined using a mixed-logit model. For the SW, the relative importance of the attributes was based on ranks and points allocated to the ‘swing’ from the worst to the best level of the attribute. The preference outcomes and self-reported response burden were directly compared between the two methods. Results Participants reported they perceived the DCE to be easier to understand and answer compared to the SW. Both methods revealed that cost and precision of the device were the most important attributes. However, the DCE had a 14.9-fold difference between the most and least important attribute, while the SW had a 1.4-fold difference. The weights derived from the SW were almost evenly distributed between all attributes. Conclusions The DCE was better received by participants, and generated larger weight differences between each attribute level, making it the more informative method in our case study. This method comparison provides further evidence of the degree of method suitability and trustworthiness.</p

Patient Preferences for Lung Cancer Treatment: A Qualitative Study Protocol Among Advanced Lung Cancer Patients

Introduction: Lung cancer is the deadliest and most prevalent cancer worldwide. Lung cancer treatments have different characteristics and are associated with a range of benefits and side effects for patients. Such differences may raise uncertainty among drug developers, regulators, payers, and clinicians regarding the value of these treatment effects to patients. The value of conducting patient preference studies (using qualitative and/or quantitative methods) for benefits and side effects of different treatment options has been recognized by healthcare stakeholders, such as drug developers, regulators, health technology assessment bodies, and clinicians. However, evidence-based guidelines on how and when to conduct and use these studies in drug decision-making are lacking. As part of the Innovative Medicines Initiative PREFER project, we developed a protocol for a qualitative study that aims to understand which treatment characteristics are most important to lung cancer patients and to develop attributes and levels for inclusion in a subsequent quantitative preference survey. Methods: The study protocol specifies a four-phased approach: (i) a scoping literature review of published literature, (ii) four focus group discussions with stage III and IV Non-Small Cell Lung Cancer patients, (iii) two nominal group discussions with stage III and IV Non-Small Cell Lung Cancer patients, and (iv) multi-stakeholder discussions involving clinicians and preference experts. Discussion: This protocol outlines methodological and practical steps as to how qualitative research can be applied to identify and develop attributes and levels for inclusion in patient preference studies aiming to inform decisions across the drug life cycle. The results of this study are intended to inform a subsequent quantitative preference survey that assesses patient trade-offs regarding lung cancer treatment options. This protocol may assist researchers, drug developers, and decision-makers in designing qualitative studies to understand which treatment aspects are most valued by patients in drug development, regulation, and reimbursement

Patient Perspectives on the Value of Patient Preference Information in Regulatory Decision Making

Background: There is increasing interest in involving patient preferences for benefits and risks in regulatory decision making. Therefore, it is essential to identify patient perspectives regarding the value of patient preference information (PPI). Objectives: The aim of this study was to explore how patients with rheumatoid arthritis (RA) value the use of PPI in regulatory decision making regarding medical products. Methods: Regulators and patients with RA were interviewed to gather initial insights into opinions on the use of PPI in regulatory decisions regarding medical products. The interviews were used to draft and validate the interview guide for focus groups with patients with RA. Participants were purposively sampled in collaboration with the Swedish Rheumatism Association in Stockholm and Uppsala. Each focus group consisted of three to six patients (18 in total). All interviews were audio-recorded, transcribed verbatim, and analysed using content analysis. Results: According to the participants, PPI could lead to regulators considering patients’ needs, lifestyles and well-being when making decisions. PPI was important in all stages of the medical product lifecycle. Participants reported that, when participating in a preference study, it is important to be well-informed about the use of the study and the development, components, administration, and risks related to the medical products. Conclusions: Patients thought PPI could be valuable to consider in regulatory decisions. It is essential for patients to be well-informed when asked for their preferences. Research on information materials to inform patients in preference studies is needed to increase the value of PPI in regulatory decision making

Research Priorities to Increase Confidence in and Acceptance of Health Preference Research:What Questions Should be Prioritized Now?

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.</p

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

Public preferences for digital health data sharing: Discrete choice experiment study in 12 european countries

Background: With new technologies, health data can be collected in a variety of different clinical, research, and public health contexts, and then can be used for a range of new purposes. Establishing the public s views about digital health data sharing is essential for policy makers to develop effective harmonization initiatives for digital health data governance at the European level. Objective: This study investigated public preferences for digital health data sharing. Methods: A discrete choice experiment survey was administered to a sample of European residents in 12 European countries (Austria, Denmark, France, Germany, Iceland, Ireland, Italy, the Netherlands, Norway, Spain, Sweden, and the United Kingdom) from August 2020 to August 2021. Respondents answered whether hypothetical situations of data sharing were acceptable for them. Each hypothetical scenario was defined by 5 attributes ("data collector," "data user," "reason for data use," "information on data sharing and consent," and "availability of review process"), which had 3 to 4 attribute levels each. A latent class model was run across the whole data set and separately for different European regions (Northern, Central, and Southern Europe). Attribute relative importance was calculated for each latent class s pooled and regional data sets. Results: A total of 5015 completed surveys were analyzed. In general, the most important attribute for respondents was the availability of information and consent during health data sharing. In the latent class model, 4 classes of preference patterns were identified. While respondents in 2 classes strongly expressed their preferences for data sharing with opposing positions, respondents in the other 2 classes preferred not to share their data, but attribute levels of the situation could have had an impact on their preferences. Respondents generally found the following to be the most acceptable: A national authority or academic research project as the data user; being informed and asked to consent; and a review process for data transfer and use, or transfer only. On the other hand, collection of their data by a technological company and data use for commercial communication were the least acceptable. There was preference heterogeneity across Europe and within European regions. Conclusions: This study showed the importance of transparency in data use and oversight of health-related data sharing for European respondents. Regional and intraregional preference heterogeneity for "data collector," "data user," "reason," "type of consent," and "review" calls for governance solutions that would grant data subjects the ability to control their digital health data being shared within different contexts. These results suggest that the use of data without consent will demand weighty and exceptional reasons. An interactive and dynamic informed consent model combined with oversight mechanisms may be a solution for policy initiatives aiming to harmonize health data use across Europe

Patient Preferences in the Medical Product Life Cycle: What do Stakeholders Think? Semi-Structured Qualitative Interviews in Europe and the USA.

Background Patient preferences (PP), which are investigated in PP studies using qualitative or quantitative methods, are a growing area of interest to the following stakeholders involved in the medical product lifecycle: academics, health technology assessment bodies,

Large-Scale Meta-GWAS Reveals Common Genetic Factors Linked to Radiation-Induced Acute Toxicities across Cancers

BACKGROUND: This study was designed to identify common genetic susceptibility and shared genetic variants associated with acute radiation-induced toxicity (RIT) across four cancer types (prostate, head and neck, breast, and lung).METHODS: A GWAS meta-analysis was performed using 19 cohorts including 12,042 patients. Acute standardized total average toxicity (rSTATacute) was modelled using a generalized linear regression model for additive effect of genetic variants adjusted for demographic and clinical covariates. LD score regression estimated shared SNP-based heritability of rSTATacute in all patients and for each cancer type.RESULTS: Shared SNP-based heritability of STATacute among all cancer types was estimated at 10% (se = 0.02), and was higher for prostate (17%, se = 0.07), head and neck (27%, se = 0.09), and breast (16%, se = 0.09) cancers. We identified 130 suggestive associated SNPs with rSTATacute (5.0x10-8&lt;P-value&lt;1.0x10-5) across 25 genomic regions. rs142667902 showed the strongest association (effect allele A; effect size -0.17; P-value=1.7x10-7), which is located near DPPA4, encoding a protein involved in pluripotency in stem cells, which are essential for repair of radiation-induced tissue injury. Gene-set enrichment analysis identified 'RNA splicing via endonucleolytic cleavage and ligation' (P = 5.1 x10-6, Pcorrected =0.079) as the top gene set associated with rSTATacute among all patients. In-silico gene expression analysis showed the genes associated with rSTATacute were statistically significantly up-regulated in skin (not sun exposed Pcorrected=0.004; sun exposed Pcorrected=0.026).CONCLUSIONS: There is shared SNP-based heritability for acute RIT across and within individual cancer sites. Future meta-GWAS among large radiotherapy patient cohorts are worthwhile to identify the common causal variants for acute radiotoxicity across cancer types.</p