A Framework for Incorporating Patient Preferences Regarding Benefits and Risks into Regulatory Assessment of Medical Technologies

Patients' Preferences for Cytoreductive Treatments in Newly Diagnosed Metastatic Prostate Cancer: The IP5-MATTER Study

BACKGROUND AND OBJECTIVE

Cytoreductive treatments for patients diagnosed with de novo synchronous metastatic hormone-sensitive prostate cancer (mHSPC) confer incremental survival benefits over systemic therapy, but these may lead to added toxicity and morbidity. Our objective was to determine patients' preferences for, and trade-offs between, additional cytoreductive prostate and metastasis-directed interventions.

METHODS

A prospective multicentre discrete choice experiment trial was conducted at 30 hospitals in the UK between December 3, 2020 and January 25, 2023 (NCT04590976). The individuals were eligible for inclusion if they were diagnosed with de novo synchronous mHSPC within 4 mo of commencing androgen deprivation therapy and had performance status 0-2. A discrete choice experiment instrument was developed to elicit patients' preferences for cytoreductive prostate radiotherapy, prostatectomy, prostate ablation, and stereotactic ablative body radiotherapy to metastasis. Patients chose their preferred treatment based on seven attributes. An error-component conditional logit model was used to estimate the preferences for and trade-offs between treatment attributes.

KEY FINDINGS AND LIMITATIONS

A total of 352 patients were enrolled, of whom 303 completed the study. The median age was 70 yr (interquartile range [IQR] 64-76) and prostate-specific antigen was 94 ng/ml (IQR 28-370). Metastatic stages were M1a 10.9% (33/303), M1b 79.9% (242/303), and M1c 7.6% (23/303). Patients preferred treatments with longer survival and progression-free periods. Patients were less likely to favour cytoreductive prostatectomy with systemic therapy (Coef. -0.448; [95% confidence interval {CI} -0.60 to -0.29]; p < 0.001), unless combined with metastasis-directed therapy. Cytoreductive prostate radiotherapy or ablation with systemic therapy, number of hospital visits, use of a "day-case" procedure, or addition of stereotactic ablative body radiotherapy did not impact treatment choice. Patients were willing to accept an additional cytoreductive treatment with 10 percentage point increases in the risk of urinary incontinence and fatigue to gain 3.4 mo (95% CI 2.8-4.3) and 2.7 mo (95% CI 2.3-3.1) of overall survival, respectively.

CONCLUSIONS AND CLINICAL IMPLICATIONS

Patients are accepting of additional cytoreductive treatments for survival benefit in mHSPC, prioritising preservation of urinary function and avoidance of fatigue.

PATIENT SUMMARY

We performed a large study to ascertain how patients diagnosed with advanced (metastatic) prostate cancer at their first diagnosis made decisions regarding additional available treatments for their prostate and cancer deposits (metastases). Treatments would not provide cure but may reduce cancer burden (cytoreduction), prolong life, and extend time without cancer progression. We reported that most patients were willing to accept additional treatments for survival benefits, in particular treatments that preserved urinary function and reduced fatigue.

Comparing Methods for Identifying Post-Market Patient Preferences at the Point of Decision-Making: Insights from Patients with Chronic Pain Considering a Spinal Cord Stimulator Device

Purpose

To compare three methods for identifying patient preferences (MIPPs) at the point of decision-making: analysis of video-recorded patient-clinician encounters, post-encounter interviews, and post-encounter surveys.

Patients and Methods

For the decision of whether to use a spinal cord stimulator device (SCS), a video coding scheme, interview guide, and patient survey were iteratively developed with 30 SCS decision-making encounters in a tertiary academic medical center pain clinic. Burke's grammar of motives was used to classify the attributed source or justification for a potential preference for each preference block. To compare the MIPPs, 13 patients' encounters with their clinician were video recorded and subsequently analyzed by 4 coders using the final video coding scheme. Six of these patients were interviewed, and 7 surveyed, immediately following their encounters.

Results

For videos, an average of 66 (range 33-106) sets of utterances potentially indicating a patient preference (a preference block), surveys 33 (range 32-34), and interviews 25 (range 18-30) were identified. Thirty-eight unique themes (75 subthemes), each a preference topic, were identified from videos, surveys 19 themes (12 subthemes), and interviews 39 themes (54 subthemes). The proportion of preference blocks that were judged as expressing a preference that was clearly important to the patient or affected their decision was highest for interviews (72.8%), surveys (68.0%), and videos (27.0%). Videos mostly attributed preferences to the patient's situation (scene) (65%); interviews, the act of receiving or living with SCS (43%); surveys, the purpose of SCS (40%).

Conclusion

MIPPs vary in the type of preferences identified and the clarity of expressed preferences in their data sets. The choice of which MIPP to use depends on projects' goals and resources, recognizing that the choice of MIPP may affect which preferences are found.

Methodological guidelines and publications of benefit-risk assessment for health technology assessment: a scoping review

OBJECTIVES

To map the available methodological guidelines and documents for conducting and reporting benefit-risk assessment (BRA) during health technologies' life cycle; and to identify methodological guidelines for BRA that could serve as the basis for the development of a BRA guideline for the context of health technology assessment (HTA) in Brazil.

DESIGN

Scoping review.

METHODS

Searches were conducted in three main sources up to March 2023: (1) electronic databases; (2) grey literature (48 HTA and regulatory organisations) and (3) manual search and contacting experts. We included methodological guidelines or publications presenting methods for conducting or reporting BRA of any type of health technologies in any context of the technology's life cycle. Selection process and data charting were conducted by independent reviewers. We provided a structured narrative synthesis of the findings.

RESULTS

From the 83 eligible documents, six were produced in the HTA context, 30 in the regulatory and 35 involved guidance for BRA throughout the technology's life cycle. We identified 129 methodological approaches for BRA in the documents. The most commonly referred to descriptive frameworks were the Problem, Objectives, Alternatives, Consequences, Trade-offs, Uncertainty, Risk and Linked decisions and the Benefit-Risk Action Team. Multicriteria decision analysis was the most commonly cited quantitative framework. We also identified the most cited metric indices, estimation and utility survey techniques that could be used for BRA.

CONCLUSIONS

Methods for BRA in HTA are less established. The findings of this review, however, will support and inform the elaboration of the Brazilian methodological guideline on BRA for HTA.

TRIAL REGISTRATION NUMBER

https://doi.org/10.17605/OSF.IO/69T3V.

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.

Pretesting Discrete-Choice Experiments: A Guide for Researchers

Discrete-choice experiments (DCEs) are a frequently used method to explore the preferences of patients and other decision-makers in health. Pretesting is an essential stage in the design of a high-quality choice experiment and involves engaging with representatives of the target population to improve the readability, presentation, and structure of the preference instrument. The goal of pretesting in DCEs is to improve the validity, reliability, and relevance of the survey, while decreasing sources of bias, burden, and error associated with preference elicitation, data collection, and interpretation of the data. Despite its value to inform DCE design, pretesting lacks documented good practices or clearly reported applied examples. The purpose of this paper is: (1) to define pretesting and describe the pretesting process specifically in the context of a DCE, (2) to present a practical guide and pretesting interview discussion template for researchers looking to conduct a rigorous pretest of a DCE, and (3) to provide an illustrative example of how these resources were operationalized to inform the design of a complex DCE aimed at eliciting tradeoffs between personal privacy and societal benefit in the context of a police method known as investigative genetic genealogy (IGG).

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.

Eliciting Exploratory Patient Preference Data: A Case Study in a Rare Disease

INTRODUCTION

Qualitative and quantitative methods provide different and complementary insights into patients' preferences for treatment.

OBJECTIVE

The aim of this study was to use a novel, mixed-methods approach employing qualitative and quantitative approaches to generate preliminary insights into patient preferences for the treatment of a rare disease-generalized myasthenia gravis (gMG).

METHODS

We conducted a mixed-methods study to collect exploratory qualitative and quantitative patient preference information and generate informative results within a condensed timeline (about 4 months). Recruitment was facilitated by an international health research firm. Study participants first reviewed a brief document describing six treatment attributes (to facilitate more efficient review of the material during the focus groups) and were then provided a link to complete an online quantitative survey with a single risk threshold task. They then participated in online focus groups, during which they discussed qualitative questions about their experience with gMG treatment and completed up to three quantitative threshold tasks, the first of which repeated the threshold task from the online survey.

RESULTS

The study elicited both quantitative data on 18 participants' risk tolerance and qualitative data on their treatment experience, additional treatment attributes of importance, the reasoning behind their preferences, and the trade-offs they were willing to make. Most participants (n = 15) chose the same hypothetical treatment in the first threshold task in the online survey and the focus groups. Focus group discussions provided insights into participants' choices in the threshold tasks, confirmed that all the attributes were relevant, and helped clarify what was important about the attributes.

CONCLUSIONS

Patient preference information can be collected using a variety of approaches, both qualitative and quantitative, tailored to fit the research needs of a study. The novel mixed-methods approach employed in this study efficiently captured patient preference data that were informative for exploratory research, internal decision making, and future research.

Association Between the Characteristics of mHealth Apps and User Input During Development and Testing: Secondary Analysis of App Assessment Data

BACKGROUND

User involvement is increasingly acknowledged as a central part of health care innovation. However, meaningful user involvement during the development and testing of mobile health apps is often not fully realized.

OBJECTIVE

This study aims to examine in which areas user input is most prevalent and whether there is an association between user inclusion and compliance with best practices for mobile health apps.

METHODS

A secondary analysis was conducted on an assessment data set of 1595 health apps. The data set contained information on whether the apps had been developed or tested with user input and whether they followed best practices across several domains. Background information was also available regarding the apps' country of origin, targeted condition areas, subjective user ratings, download numbers, and risk (as per the National Institute for Health and Care Excellence Evidence Standards Framework [ESF]). Descriptive statistics, Mann-Whitney U tests, and Pearson chi-square analyses were applied to the data.

RESULTS

User involvement was reported by 8.71% (139/1595) of apps for only the development phase, by 33.67% (537/1595) of apps for only the testing phase, by 21.88% (349/1595) of apps for both phases, and by 35.74% (570/1595) of apps for neither phase. The highest percentage of health apps with reported user input during development was observed in Denmark (19/24, 79%); in the condition areas of diabetes (38/79, 48%), cardiology (15/32, 47%), pain management (20/43, 47%), and oncology (25/54, 46%); and for high app risk (ESF tier 3a; 105/263, 39.9%). The highest percentage of health apps with reported user input during testing was observed in Belgium (10/11, 91%), Sweden (29/34, 85%), and France (13/16, 81%); in the condition areas of neurodiversity (42/52, 81%), respiratory health (58/76, 76%), cardiology (23/32, 72%), and diabetes (56/79, 71%); and for high app risk (ESF tier 3a; 176/263, 66.9%). Notably, apps that reported seeking user input during testing demonstrated significantly more downloads than those that did not (P=.008), and user inclusion was associated with better compliance with best practices in clinical assurance, data privacy, risk management, and user experience.

CONCLUSIONS

The countries and condition areas in which the highest percentage of health apps with user involvement were observed tended to be those with higher digital maturity in health care and more funding availability, respectively. This suggests that there may be a trade-off between developers' willingness or ability to involve users and the need to meet challenges arising from infrastructure limitations and financial constraints. Moreover, the finding of a positive association between user inclusion and compliance with best practices indicates that, where no other guidance is available, users may benefit from prioritizing health apps developed with user input as the latter may be a proxy for broader app quality.

Maximum Acceptable Risk Estimation Based on a Discrete Choice Experiment and a Probabilistic Threshold Technique

OBJECTIVE

We aimed to empirically compare maximum acceptable risk results estimated using both a discrete choice experiment (DCE) and a probabilistic threshold technique (PTT).

METHODS

Members of the UK general public (n = 982) completed an online survey including a DCE and a PTT (in random order) measuring their preferences for preventative treatment for rheumatoid arthritis. For the DCE, a Bayesian D-efficient design consisting of four blocks of 15 choice tasks was constructed including six attributes with varying levels. The PTT used identical risk and benefit attributes. For the DCE, a panel mixed-logit model was conducted, both mean and individual estimates were used to calculate maximum acceptable risk. For the PTT, interval regression was used to calculate maximum acceptable risk. Perceived complexity of the choice tasks and preference heterogeneity were investigated for both methods.

RESULTS

Maximum acceptable risk confidence intervals of both methods overlapped for serious infection and serious side effects but not for mild side effects (maximum acceptable risk was 32.7 percent-points lower in the PTT). Although, both DCE and PTT tasks overall were considered easy or very easy to understand and answer, significantly more respondents rated the DCE choice tasks as easier to understand compared with those who rated the PTT as easier (7-percentage point difference; p < 0.05).

CONCLUSIONS

Maximum acceptable risk estimate confidence intervals based on a DCE and a PTT overlapped for two out of the three included risk attributes. More respondents rated the DCE as easier to understand. This may suggest that the DCE is better suited in studies estimating maximum acceptable risk for multiple risk attributes of differing severity, while the PTT may be better suited when measuring heterogeneity in maximum acceptable risk estimates or when investigating one or more serious adverse events.

A systematic review of models of patient engagement in the development and life cycle management of medicines

There is currently no universally agreed code of practice for patient engagement (PE), and existing guidelines do not fully cover the scope across medicine development and subsequent life cycle management. This review conceptualises the meaning and summarises the current models of PE. A systematic literature review was conducted and analysed by thematic synthesis. Eight themes were identified as components of how to achieve meaningful PE, and five were identified for where to engage with patients in drug development. This review provides summative guidance for stakeholders intending to introduce PE and establishes a starting point for the development of a universal code of practice.

Adaptation of the WOMAC for Use in a Patient Preference Study

OBJECTIVES

To adapt a patient-reported outcome (PRO) measure, the Western Ontario McMaster Universities Osteoarthritis Index (WOMAC), into efficacy attributes for a discrete choice experiment (DCE) survey designed to quantify the relative importance of endpoints commonly used in knee osteoarthritis (KOA) trials.

METHODS

The adaptation comprised four steps: (1) selecting domains of interest; (2) determining presentation and framing of selected attributes; (3) determining attribute levels; and (4) developing choice tasks. This process involved input from multiple stakeholders, including regulators, health preference researchers, and patients. Pretesting was conducted to evaluate if patients comprehended the adapted survey attributes and could make trade-offs among them.

RESULTS

The WOMAC pain and function domains were selected for adaption to two efficacy attributes. Two versions of the discrete choice experiment (DCE) instrument were created to compare efficacy using (1) total domain scores and (2) item scores for "walking on a flat surface." Both attributes were presented as improvement from baseline scores by levels of 0%, 30%, 50%, and 100%. Twenty-six participants were interviewed in a pretest of the instrument (average age 60 years; 58% female; 62% had KOA for ≥ 5 years). The participants found both versions of attributes meaningful and relevant for treatment decision-making. They demonstrated willingness and ability to tradeoff improvements in pain and function separately, though many perceived them as inter-related.

CONCLUSIONS

This study adds to the growing literature regarding adapting PRO measures for patient preference studies. Such adaptation is important for designing a preference study that can incorporate a clinical trial's outcomes with PRO endpoints.

Taking the Shortcut: Simplifying Heuristics in Discrete Choice Experiments

Health-related discrete choice experiments (DCEs) information can be used to inform decision-making on the development, authorisation, reimbursement and marketing of drugs and devices as well as treatments in clinical practice. Discrete choice experiment is a stated preference method based on random utility theory (RUT), which imposes strong assumptions on respondent choice behaviour. However, respondents may use choice processes that do not adhere to the normative rationality assumptions implied by RUT, applying simplifying decision rules that are more selective in the amount and type of processed information (i.e., simplifying heuristics). An overview of commonly detected simplifying heuristics in health-related DCEs is lacking, making it unclear how to identify and deal with these heuristics; more specifically, how researchers might alter DCE design and modelling strategies to accommodate for the effects of heuristics. Therefore, the aim of this paper is three-fold: (1) provide an overview of common simplifying heuristics in health-related DCEs, (2) describe how choice task design and context as well as target population selection might impact the use of heuristics, (3) outline DCE design strategies that recognise the use of simplifying heuristics and develop modelling strategies to demonstrate the detection and impact of simplifying heuristics in DCE study outcomes.

Patient and General Population Preferences Regarding the Benefits and Harms of Treatment for Metastatic Prostate Cancer: A Discrete Choice Experiment

Background

Patient preferences for treatment outcomes are important to guide decision-making in clinical practice, but little is known about the preferences of patients with metastatic hormone-sensitive prostate cancer (mHSPC).

Objective

To evaluate patient preferences regarding the attributed benefits and harms of systemic treatments for mHSPC and preference heterogeneity between individuals and specific subgroups.

Design setting and participants

We conducted an online discrete choice experiment (DCE) preference survey among 77 patients with metastatic prostate cancer (mPC) and 311 men from the general population in Switzerland between November 2021 and August 2022.

Outcome measurements and statistical analysis

We evaluated preferences and preference heterogeneity related to survival benefits and treatment-related adverse effects using mixed multinomial logit models and estimated the maximum survival time participants were willing to trade to avert specific adverse effects. We further assessed characteristics associated with different preference patterns via subgroup and latent class analyses.

Results and limitations

Patients with mPC showed an overall stronger preference for survival benefits in comparison to men from the general population (p = 0.004), with substantial preference heterogeneity between individuals within the two samples (both p < 0.001). There was no evidence of differences in preferences for men aged 45-65 yr versus ≥65 yr, patients with mPC in different disease stages or with different adverse effect experiences, or general population participants with and without experiences with cancer. Latent class analyses suggested the presence of two groups strongly preferring either survival or the absence of adverse effects, with no specific characteristic clearly associated with belonging to either group. Potential biases due to participant selection, cognitive burden, and hypothetical choice scenarios may limit the study results.

Conclusions

Given the relevant heterogeneity in participant preferences regarding the benefits and harms of treatment for mHSPC, patient preferences should be explicitly discussed during decision-making in clinical practice and reflected in clinical practice guidelines and regulatory assessment regarding treatment for mHSPC.

Patient summary

We examined the preferences (values and perceptions) of patients and men from the general population regarding the benefits and harms of treatment for metastatic prostate cancer. There were large differences between men in how they balanced the expected survival benefits and potential adverse effects. While some men strongly valued survival, others more strongly valued the absence of adverse effects. Therefore, it is important to discuss patient preferences in clinical practice.

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.

Method for Calculating the Simultaneous Maximum Acceptable Risk Threshold (SMART) from Discrete-Choice Experiment Benefit-Risk Studies

BACKGROUND

Medical decisions require weighing expected benefits of treatment against multiple adverse outcomes under uncertainty (i.e., risks) that must be accepted as a bundle. However, conventional maximum acceptable risk (MAR) estimates derived from discrete-choice experiment benefit-risk studies evaluate the acceptance of individual risks, assuming other risks are fixed, potentially leading decision makers to misinterpret levels of risk acceptance.

DESIGN

Using simulations and a published discrete-choice experiment, we demonstrate a method for identifying multidimensional risk-tolerance measures given a treatment level of benefit.

RESULTS

Simultaneous Maximum Acceptable Risk Thresholds (SMART) represents combinations of risks that would be jointly accepted in exchange for specific treatment benefits. The framework shows how the expectation of utility associated with treatments that involve multiple risks are related even when preferences for potential adverse events are independent. We find that the form of the marginal effects of adverse-event probabilities on the expected utility of treatment determines the magnitude of differences between SMART and conventional single-outcome MAR estimates.

LIMITATIONS

Preferences for potential adverse events not considered in a study or preferences for adverse-event attributes held constant in risk-tolerance calculations may affect estimated risk tolerance. Further research is needed to understand the right balance between realistically reflecting clinical treatments with many potential adverse events and the cognitive burden of evaluating risk-risk tradeoffs in research and in practice.

CONCLUSIONS AND IMPLICATIONS

SMART analysis should be considered in preference studies evaluating the joint acceptance of multiple potential adverse events.

HIGHLIGHTS

Conventional approaches to calculate maximum-acceptable risk (MAR) using discrete-choice experiment data account for 1 adverse-event risk at a time, requiring that decision makers infer the acceptability of treatments when patients are exposed to multiple risks simultaneously.The Simultaneous Maximum Acceptable Risk Threshold (SMART) maps combinations of adverse-event risks that would be jointly acceptable given a specific treatment benefit and provides a transparent and precise portrayal of acceptance of multiple risks.Risk levels that would be accepted using individual MAR estimates might not be acceptable when simultaneous risks are considered, especially when marginal expected disutility of risk is decreasing nonlinearly with risk probabilities.Preference researchers should calculate SMARTs in any discrete-choice study in which 2 or more adverse-event risks are presented, particularly if risk preferences are nonlinear.

Patient-Preference Diagnostics: Adapting Stated-Preference Methods to Inform Effective Shared Decision Making

BACKGROUND

While clinical practice guidelines underscore the need to incorporate patient preferences in clinical decision making, incorporating meaningful assessment of patient preferences in clinical encounters is challenging. Structured approaches that combine quantitative patient preferences and clinical evidence could facilitate effective patient-provider communication and more patient-centric health care decisions. Adaptive conjoint or stated-preference approaches can identify individual preference parameters, but they can require a relatively large number of choice questions or simplifying assumptions about the error with which preferences are elicited.

METHOD

We propose an approach to efficiently diagnose preferences of patients for outcomes of treatment alternatives by leveraging prior information on patient preferences to generate adaptive choice questions to identify a patient's proximity to known preference phenotypes. This information can be used for measuring sensitivity and specificity, much like any other diagnostic procedure. We simulated responses with varying levels of choice errors for hypothetical patients with specific preference profiles to measure sensitivity and specificity of a 2-question preference diagnostic.

RESULTS

We identified 4 classes representing distinct preference profiles for patients who participated in a previous first-time anterior shoulder dislocation (FTASD) survey. Posterior probabilities of class membership at the end of a 2-question sequence ranged from 87% to 89%. We found that specificity and sensitivity of the 2-question sequences were robust to respondent errors. The questions appeared to have better specificity than sensitivity.

CONCLUSIONS

Our results suggest that this approach could help diagnose patient preferences for treatments for a condition such as FTASD with acceptable precision using as few as 2 choice questions. Such preference-diagnostic tools could be used to improve and document alignment of treatment choices and patient preferences.

HIGHLIGHTS

Approaches that combine patient preferences and clinical evidence can facilitate effective patient-provider communication and more patient-centric healthcare decisions. However, diagnosing individual-level preferences is challenging, and no formal diagnostic tools exist.We propose a structured approach to efficiently diagnose patient preferences based on prior information on the distribution of patient preferences in a population.We generated a 2-question test of preferences for the outcomes associated with the treatment of first-time anterior shoulder dislocation.The diagnosis of preferences can help physicians discuss relevant aspects of the treatment options and proactively address patient concerns during the clinical encounter.

A Roadmap for Increasing the Usefulness and Impact of Patient-Preference Studies in Decision Making in Health: A Good Practices Report of an ISPOR Task Force

Many qualitative and quantitative methods are readily available to study patient preferences in health. These methods are now being used to inform a wide variety of decisions, and there is a growing body of evidence showing studies of patient preferences can be used for decision making in a wide variety of contexts. This ISPOR Task Force report synthesizes current good practices for increasing the usefulness and impact of patient-preference studies in decision making. We provide the ISPOR Roadmap for Patient Preferences in Decision Making that invites patient-preference researchers to work with decision makers, patients and patient groups, and other stakeholders to ensure that studies are useful and impactful. The ISPOR Roadmap consists of 5 key elements: (1) context, (2) purpose, (3) population, (4) method, and (5) impact. In this report, we define these 5 elements and provide good practices on how patient-preference researchers and others can actively contribute to increasing the usefulness and impact of patient-preference studies in decision making. We also present a set of key questions that can support researchers and other stakeholders (eg, funders, reviewers, readers) to assess efforts that promote the ongoing impact (both intended and unintended) of a particular preference study and additional studies in the future.

Prosthesis preferences for those with upper limb loss: Discrete choice study of PULLTY® for use in regulatory decisions

Introduction

The patient's voice in shared decision-making has progressed from physician's office to regulatory decision-making for medical devices with FDA's Patient Preference Initiative. A discrete-choice preference measure for upper limb prosthetic devices was developed to investigate patient's risk/benefit preference choices for regulatory decision making.

Methods

Rapid ethnographic procedures were used to design a discrete-choice measure describing risk and benefits of osseointegration with myoelectric control and test in a pilot preference study in adults with upper limb loss. Primary outcome is utility of each choice based conjoint (CBC) attribute using mixed-effects regression. Utilities with and without video, and between genders were compared.

Results

Strongest negative preference was for avoiding infection risk (B = -1.77, p < 0.001) and chance of daily pain (B = -1.22, p, 0.001). Strongest positive preference was for attaining complete independence when cooking dinner (B = 1.62, p < 0.001) and smooth grip patterns at all levels (B = 1.62, B = 1.28, B = 1.26, p < 0.001). Trade-offs showed a 1% increase in risk of serious/treatable infection resulted in a 1.77 decrease in relative preference. There were gender differences, and where video was used, preferences were stronger.

Conclusions

Strongest preferences were for attributes of functionality and independence versus connectedness and sensation but showed willingness to make risk-benefit trade-offs. Findings provide valuable information for regulatory benefit-risk decisions for prosthetic device innovations.

Trial Registration

This study is not a clinical trial reporting results of a health care intervention so is not registered.

The two-bucket problem of unproven stem cell interventions

The two-bucket problem of unproven stem cell interventions (SCIs) continues to bifurcate good (ethical) from bad (unethical) practices in the translation of stem cell medicine in ways that divert attention from other salient and challenging questions. It causes scholars to focus narrowly on reprimanding bad actors through legal and regulatory approaches and distracts from other important considerations such as how best to balance evidence with unmet patient needs and address misinformation about unproven stem cell interventions potentially changing patient behavior. The stem cell science community needs to consider a range of ethical practices and aim to address important questions that have yet not received sufficient consideration.

Leveraging Patient Preference Information in Medical Device Clinical Trial Design

Use of robust, quantitative tools to measure patient perspectives within product development and regulatory review processes offers the opportunity for medical device researchers, regulators, and other stakeholders to evaluate what matters most to patients and support the development of products that can best meet patient needs. The medical device innovation consortium (MDIC) undertook a series of projects, including multiple case studies and expert consultations, to identify approaches for utilizing patient preference information (PPI) to inform clinical trial design in the US regulatory context. Based on these activities, this paper offers a cogent review of considerations and opportunities for researchers seeking to leverage PPI within their clinical trial development programs and highlights future directions to enhance this field. This paper also discusses various approaches for maximizing stakeholder engagement in the process of incorporating PPI into the study design, including identifying novel endpoints and statistical considerations, crosswalking between attributes and endpoints, and applying findings to the population under study. These strategies can help researchers ensure that clinical trials are designed to generate evidence that is useful to decision makers and captures what matters most to patients.

Rare diseases and space health: optimizing synergies from scientific questions to care

Knowledge transfer among research disciplines can lead to substantial research progress. At first glance, astronaut health and rare diseases may be seen as having little common ground for such an exchange. However, deleterious health conditions linked to human space exploration may well be considered as a narrow sub-category of rare diseases. Here, we compare and contrast research and healthcare in the contexts of rare diseases and space health and identify common barriers and avenues of improvement. The prevalent genetic basis of most rare disorders contrasts sharply with the occupational considerations required to sustain human health in space. Nevertheless small sample sizes and large knowledge gaps in natural history are examples of the parallel challenges for research and clinical care in the context of both rare diseases and space health. The two areas also face the simultaneous challenges of evidence scarcity and the pressure to deliver therapeutic solutions, mandating expeditious translation of research knowledge into clinical care. Sharing best practices between these fields, including increasing participant involvement in all stages of research and ethical sharing of standardized data, has the potential to contribute to humankind's efforts to explore ever further into space while caring for people on Earth in a more inclusive fashion.

Methods to Summarize Discrete-Choice Experiments in a Systematic Review: A Scoping Review

BACKGROUND AND OBJECTIVE

Systematic reviews of discrete-choice experiments (DCEs) are being increasingly conducted. The objective of this scoping review was to identify and describe the methodologies that have been used to summarize results across DCEs.

METHODS

We searched the electronic databases MEDLINE and EMBASE from inception to March 18, 2021, to identify English-language systematic reviews of patient preferences that included at least two DCEs and extracted data on attribute importance. The methods used to summarize results across DCEs were classified into narrative, semi-quantitative, and quantitative (meta-analytic) approaches and compared. Approaches to characterize the extent of preference heterogeneity were also described.

RESULTS

From 7362 unique records, we identified 54 eligible reviews from 2010 to Mar 2021, across a broad range of health conditions. Most (83%) used a narrative approach to summarize findings of DCEs, often citing differences in studies as the reason for not formally pooling findings. Semi-quantitative approaches included summarizing the frequency of the most important attributes, the frequency of attribute statistical significance, or tabulated comparisons of attribute importance for each pair of attributes. One review conducted a meta-analysis using the maximum acceptable risk. While reviews often commented on the heterogeneity of patient preferences, few (6%) addressed this systematically across studies.

CONCLUSION

While not commonly used, several semi-quantitative and one quantitative approach for synthesizing results of DCEs were identified, which may be useful for generating summary estimates across DCEs when appropriate. Further work is needed to assess the validity and usefulness of these approaches.

A stated preference survey to explore patient preferences for novel preventive migraine treatments

OBJECTIVE

The objective of this study was to explore patient preference for attributes of calcitonin gene-related peptide (CGRP) inhibitors for the preventive treatment of migraine and to describe differences in treatment preferences between patients.

BACKGROUND

CGRP inhibitors are a novel class of migraine drugs specifically developed for the preventive treatment of migraine. Clinicians should understand patient preferences for CGRP inhibitors to inform and support prescribing choices.

METHODS

Patients with migraine in the US and Germany were recruited to participate in an online discrete choice experiment (DCE) survey, which presented hypothetical treatment choices using five attributes: mode of administration, side effects, migraine frequency, migraine severity, and consistency of treatment effectiveness. Attribute selection was informed by a literature review and semi-structured patient interviews (n = 35), and evaluated using patient cognitive debriefing interviews (n = 5).

RESULTS

Of 680 who consented to participate, 506 participants completed the survey and were included in the study (US = 257; Germany = 249). Overall, participants placed highest importance (preference weight, beta = 1.65, p < 0.001) on the treatment's ability to reduce the severity of migraine (mild vs. unchanged severity), followed by consistent treatment effectiveness (beta = 1.13, p < 0.001), and higher chance of reduced migraine frequency (beta = 1.00, p < 0.001). Participants preferred an oral tablet every other day (beta = 1.00, p < 0.001) over quarterly infusion, quarterly injections (p = 0.019), or monthly injection (p < 0.001). Preference for all treatment attributes were heterogeneous, and the subgroup analyses found that participants naïve to CGRP monoclonal antibody treatments had a stronger preference for oral therapy compared to those with such experience (p = 0.006).

CONCLUSION

In this DCE assessing CGRP inhibitors attributes, the main driver of patient choice was treatment effectiveness, specifically reduced migraine severity, and consistent treatment effectiveness. Further, patients exhibited an overall preference for an oral tablet every other day over injectables. Patients' experience with previous treatments informs the value they place on treatment characteristics.

How to balance valuable innovation with affordable access to medicines in Belgium?

Background: Countries are struggling to provide affordable access to medicines while supporting the market entry of innovative, expensive products. This Perspective aims to discuss challenges and avenues for balancing health care system objectives of access, affordability and innovation related to medicines in Belgium (and in other countries). Methods: This Perspective focuses on the R&D, regulatory approval and market access phases, with particular attention to oncology medicines, precision medicines, orphan medicines, advanced therapies, repurposed medicines, generics and biosimilars. The authors conducted a narrative review of the peer-reviewed literature, of the grey literature (such as policy documents and reports of consultancy agencies), and of their own research. Results: Health care stakeholders need to consider various initiatives for balancing innovation with access to medicines, which relate to clinical and non-clinical outcomes (e.g. supporting the conduct of pragmatic clinical trials, treatment optimisation and patient preference studies, optimising the use of real-world evidence in market access decision making), value assessment (e.g. increasing the transparency of the reimbursement system and criteria, tailoring the design of managed entry agreements to specific types of uncertainty), affordability (e.g. harnessing the role of generics and biosimilars in encouraging price competition, maximising opportunities for personalising and repurposing medicines) and access mechanisms (e.g. promoting collaboration and early dialogue between stakeholders including patients). Conclusion: Although there is no silver bullet that can balance valuable innovation with affordable access to medicines, (Belgian) policy and decision makers should continue to explore initiatives that exploit the potential of both the on-patent and off-patent pharmaceutical markets.

Impact of adalimumab on disease burden in moderate-to-severe ulcerative colitis patients: The one-year, real-world UCanADA study

BACKGROUND

A gap remains in documenting the impact of anti-tumor necrosis factor therapy on disease burden in ulcerative colitis (UC) patients treated in a real-world setting. The use of patient-reported outcomes (PROs) has been discussed as a primary endpoint in the context of the FDA PRO Guidance, for labelling purposes. Specifically, the efficacy and safety of adalimumab have been demonstrated in pivotal trials; however, data are needed to understand how clinical results translate into improvements in key aspects of the daily lives of UC patients, such as symptoms, health-related quality of life (HRQoL), and disability.

AIM

To assess real-world effectiveness of adalimumab on PRO measures in patients with moderate-to-severe UC.

METHODS

UCanADA was a single arm, prospective, 1-year multicenter Canadian post-marketing observational study in which multiple PRO questionnaires were completed—with psychologic distress/depression symptoms as the primary endpoint—by patients with moderate-to-severe UC. Assessments were performed during patients’ routine care visit schedule, which was at the initiation of adalimumab (baseline), after induction (approximately 8 wk), and 52 wk after baseline. Additional optional assessments between weeks 8 and 52 were collected at least once but no more than two times during this period. Serious safety events and per-protocol adverse events were collected.

RESULTS

From 23 Canadian centres, 100 patients were enrolled and 48 completed the study. Measured with the Patient Health Questionnaire–9 items at week 52, 61.5% (40/65) [95% confidence interval (CI): 49.7%-73.4%] of the patients improved in psychologic distress/depression symptoms, which was slightly higher in completers [65.9% (29/44); 95%CI: 51.9%-79.9%)]. At week 52, clinical response and clinical remission were achieved respectively by 65.7% (44/73) and 47.8% (32/73) of the patients. The odds of improving depressive symptoms for those achieving a clinical remission at week 52 was 7.94 higher compared with those not achieving a clinical remission (CI: 1.42, 44.41; P = 0.018). Significant changes from baseline to weeks 8 and 52 were observed in disability, HRQoL, and fatigue. Meaningful improvement was reported in work impairment.

CONCLUSION

At week 52, over 60% of the UCanADA patients had depressive symptoms significantly reduced, as well as HRQoL, fatigue symptoms, and work impairment improved. No new safety signals were detected.

How to calculate the life cycle of high-risk medical devices for patient safety

In this study, we analyzed Korean and foreign systems, focusing on high-risk medical devices that urgently need to be managed, and we present an life cycle calculation method for determining replacement time. A literature review was conducted to confirm the regulations of the medical device management system and life cycle by country, and a case analysis was performed to verify the replacement evaluation criteria of actual medical institutions. In addition, durability data from the Public Procurement Service, American Hospital Association, and Samsung Medical Center were used to calculate the life cycle of high-risk medical devices. The analysis showed that in the case of Korean and foreign medical device regulatory agencies, there were no specific life cycle regulations for high-risk medical devices. In addition, the important items in the medical device replacement evaluation were found to be the year of introduction, repair cost, component discontinuation, and several failures. On calculating the life cycle of high-risk medical devices revealed that the replacement time is 13 years for anesthesia machines, 14 years for defibrillators, 16 years for heart-lung machines, and 13 years for ventilators. To introduce a uniform medical device replacement standard and life cycle calculation method, the government will need to reorganize the medical device replacement laws and systems. In addition, in the case of medical institutions, it is necessary to secure patient safety by using expert groups to prepare specific life cycle standards that consider the characteristics of medical devices.

Psychosocial Factors Are Associated With Risk Acceptance in Upper Extremity Patients

BACKGROUND

Patients who help choose their health strategies are more adherent and achieve better health. An important role of the clinician is to verify that a patient's expressed preferences are consistent with what matters most to the patient and not muddled by common misconceptions about symptoms or conditions. Patient choices are influenced by estimation of the potential benefits and potential harms of a given intervention. One method for quantifying these estimations is the concept of maximum acceptable risk (MAR), or the maximum risk that subjects are willing to accept in exchange for a given therapeutic benefit. This study addressed the hypothesis that misconceptions due to unhelpful cognitive bias regarding pain are associated with risk acceptance among people seeking care for an upper extremity condition.

METHODS

We invited 140 new adult patients visiting an upper extremity specialist to complete a survey including demographics, pain intensity, depression and anxiety symptoms, catastrophic thinking, activity limitations, and MAR. Trauma or nontrauma diagnosis was obtained from the treating clinician and recorded by the research assistant. We used bivariate and linear regression analyses to identify factors associated with MAR among this population.

RESULTS

Accounting for potential confounding in multivariable analysis, higher MAR was associated with older age and greater catastrophic thinking.

CONCLUSIONS

Specialists can be aware that people with more unhelpful cognitive biases may be willing to take more risk. Vigilance for common misconceptions and gentle, incremental reorientation of those misconceptions can increase the probability that people will choose options consistent with what matters most to them.

The Patient Voice: Exploring Treatment Preferences in Participants with Mild Cognitive Concerns to Inform Regulatory Decision Making

OBJECTIVE

We aimed to assess the feasibility of developing a discrete-choice experiment survey to elicit preferences for a treatment to delay cognitive decline among people with a clinical syndrome consistent with early Alzheimer's disease, including the development of self-reported screening criteria to recruit the sample.

METHODS

Using input from qualitative interviews, we developed a discrete-choice experiment survey containing a multifaceted beneficial treatment attribute related to slowing cognitive decline for respondents with self-reported cognitive concerns. In two rounds of in-person pretest interviews, we tested and revised the survey text and discrete-choice experiment questions, including examples, language, and levels associated with the Alzheimer's Disease Assessment Scale-Cognitive Subscale, along with a set of de novo self-reported questions for identifying respondents who had neither too mild nor too advanced cognitive decline. Self-reported memory and thinking problems were compared with symptoms from studies of patients with early Alzheimer's disease (e.g., mild cognitive impairment, mild Alzheimer's disease) to determine whether those studies' recruited patients were similar to our anticipated target population. Round 1 pretest interviews resulted in significant simplifications in the survey instrument, revisions to the inclusion and exclusion criteria, and revisions to the screening process. In round 2 of the pretest interviews, the ability of participants to provide consistent responses to the self-reported screening questions was further assessed. In addition, to evaluate participants' ability to understand and independently complete the discrete-choice experiment survey, two interviewers independently evaluated each participant's ability to make trade-offs in the discrete-choice experiment questions and to understand the content of the survey.

RESULTS

Round 1 (15 pretest interviews) identified challenges with the survey instrument related to the complexity of the choice questions. The screening process did not screen out seven respondents with more advanced cognitive decline, as determined qualitatively by the interviewers and by these participants' inability to complete the survey. The survey instrument and screening criteria were revised, and an initial online screener was added to the screening process before round 2 pretests. In round 2 pretests, 12 participants reported cognitive problems similar to the target population for the survey but were judged able to understand and independently complete the discrete-choice experiment survey.

CONCLUSIONS

We developed self-reported screening criteria that identified a sample of individuals with memory and thinking concerns who were similar to individuals with clinical symptoms of early Alzheimer's disease and who were able to independently complete a simplified discrete-choice experiment survey. Quantitative patient preference studies provide important information on patients' willingness to trade off treatment benefits/risks. Adapting the technique for patients with cognitive decline requires careful testing and adjustments to survey instruments. This work suggests it is the severity of cognitive impairment, rather than its presence, that determines the ability to complete a simplified discrete-choice experiment survey.

Methodology to derive preference for health screening programmes using discrete choice experiments: a scoping review

BACKGROUND

While involving users in healthcare decision-making has become increasingly common and important, there is a lack of knowledge about how to best design community-based health screening programs. Reviews of methods that incorporate discrete choice experiments (DCEs) are scarce, particularly for non-cancer illnesses like cardiovascular disease, diabetes and liver disease. We provide an overview of currently available applications and methods available by using DCEs in health screening programs, for chronic conditions.

METHODS

A scoping review was undertaken, where four electronic databases were searched for key terms to identify eligible DCE studies related to community health screening. We included studies that met a pre-determined criteria, including being published between 2011 and 2021, in English and reported findings on human participants. Data were systematically extracted, tabulated, and summarised in a narrative review.

RESULTS

A total of 27 studies that used a DCE to elicit preferences for cancer (n = 26) and cardiovascular disease screening (n = 1) programmes were included in the final analysis. All studies were assessed for quality, against a list of 13 criteria, with the median score being 9/13 (range 5-12). Across the 27 studies, the majority (80%) had the same overall scores. Two-thirds of included studies reported a sample size calculation, approximately half (13/27) administered the survey completely online and over 75% used the general public as the participating population.

CONCLUSION

Our review has led to highlighting several areas of current practice that can be improved, particularly greater use of sample size calculations, increased use of qualitative methods, better explanation of the chosen experimental design including how choice sets are generated, and methods for analysis.

What matters most to patients with severe aortic stenosis when choosing treatment? Framing the conversation for shared decision making

Background

Guidelines recommend including the patient’s values and preferences when choosing treatment for severe aortic stenosis (sAS). However, little is known about what matters most to patients as they develop treatment preferences. Our objective was to identify, prioritize, and organize patient-reported goals and features of treatment for sAS.

Methods

This multi-center mixed-methods study conducted structured focus groups using the nominal group technique to identify patients’ most important treatment goals and features. Patients separately rated and grouped those items using card sorting techniques. Multidimensional scaling and hierarchical cluster analyses generated a cognitive map and clusters.

Results

51 adults with sAS and 3 caregivers with experience choosing treatment (age 36–92 years) were included. Participants were referred from multiple health centers across the U.S. and online. Eight nominal group meetings generated 32 unique treatment goals and 46 treatment features, which were grouped into 10 clusters of goals and 11 clusters of features. The most important clusters were: 1) trust in the healthcare team, 2) having good information about options, and 3) long-term outlook. Other clusters addressed the need for and urgency of treatment, being independent and active, overall health, quality of life, family and friends, recovery, homecare, and the process of decision-making.

Conclusions

These patient-reported items addressed the impact of the treatment decision on the lives of patients and their families from the time of decision-making through recovery, homecare, and beyond. Many attributes had not been previously reported for sAS. The goals and features that patients’ value, and the relative importance that they attach to them, differ from those reported in clinical trials and vary substantially from one individual to another. These findings are being used to design a shared decision-making tool to help patients and their clinicians choose a treatment that aligns with the patients’ priorities.

Trial registration

ClinicalTrials.gov, Trial ID: NCT04755426, Trial URL https://clinicaltrials.gov/ct2/show/NCT04755426.

The Role of Attribute Screening and Choice Set Formation in Health Discrete Choice Experiments: Modeling the Impact of Benefit and Risk Attributes

OBJECTIVES

This study aimed to demonstrate the econometric modeling of benefit/risk-based choice set formation (CSF) within health-related discrete choice experiments.

METHODS

In 4 different case studies, first, a trade-off model was fitted; building on this, a screening model was fitted; and finally, a full CSF model was estimated. This final model allows for attributes to be used first to screen out alternatives from choice tasks before respondents' trade-off attributes and make a choice among feasible alternatives. Educational level and health literacy of respondents were accounted for in all models.

RESULTS

Model fit in terms of log likelihood, pseudo-R², Akaike information criterion, and Bayesian information criterion improved from using only trade-off or screening models compared with CSF models in 3 of the 4 case studies. In those studies, significant screening behavior was identified that (1) affected trade-off inferences, (2) rejects the pure trade-off model, and (3) supports the existence of screening on the basis of benefit-risk profiles, and other attributes. Educational level and health literacy showed significant interactions with multiple attributes in all case studies.

CONCLUSIONS

Choice modelers should pay close attention to noncompensatory respondent behavior when they include benefit or risk attributes in their discrete choice experiment. Further studies should investigate why and when respondents undertake screening behavior. Screening behavior in choice data analysis is always a possibility, so researchers should explore extensions of econometric models to reflect noncompensatory behavior. Assuming that benefit and risk attributes will only affect trade-off behavior is likely to lead to biased conclusions about benefit or risk-based behavior.

Development of a Patient Preference Survey for Wearable Kidney Replacement Therapy Devices

Background

Recent innovations have the potential to disrupt the current paradigm for kidney failure treatment. The US Food and Drug Administration is committed to incorporating valid scientific evidence about how patients weigh the benefits and risks of new devices into their decision making, but to date, premarket submission of patient preference information (PPI) has been limited for kidney devices. With input from stakeholders, we developed a survey intended to yield valid PPI, capturing how patients trade off the potential benefits and risks of wearable dialysis devices and in-center hemodialysis.

Methods

We conducted concept elicitation interviews with individuals receiving dialysis to inform instrument content. After instrument drafting, we conducted two rounds of pretest interviews to evaluate survey face validity, comprehensibility, and perceived relevance. We pilot tested the survey with in-center hemodialysis patients to assess comprehensibility and usability further. Throughout, we used participant input to guide survey refinements.

Results

Thirty-six individuals receiving in-center or home dialysis participated in concept elicitation (N=20) and pretest (N=16) interviews. Participants identified reduced fatigue, lower treatment burden, and enhanced freedom as important benefits of a wearable device, and many expressed concerns about risks related to device disconnection-specifically bleeding and infection. We drafted a survey that included descriptions of the risks of serious bleeding and serious infection and an assessment of respondent willingness to wait for a safer device. Input from pretest interviewees led to various instrument modifications, including treatment descriptions, item wording, and risk-level explanations. Pilot testing of the updated survey among 24 in-center hemodialysis patients demonstrated acceptable survey comprehensibility and usability, although 50% of patients required some assistance.

Conclusions

The final survey is a 54-item web-based instrument that will yield estimates of the maximal acceptable risk for the described wearable device and willingness to wait for wearable devices with lower risk.

Preference Testing in Medical Devices: Current Framework and Regulatory Gaps

Preference testing is a valuable source of information that can be provided by both healthcare professionals (HCPs) and patients (users). It can be used to improve the design and development of medical devices by feeding into device usability and, ultimately, risk management. Furthermore, it can aid with selecting the most appropriate clinical endpoints to be used in the clinical evaluation of a device and increase patient engagement by incorporating patient-relevant outcomes. Preference testing is widely conducted in the food industry but is not widespread in the medical field due to limited guidelines and a lack of regulatory framework. As such, manufacturers may be unaware of the benefits of preference testing and fail to take full advantage of it, or conversely, may use inappropriate methodology and/or analyses and consequently fail to collect meaningful data. In this position paper, we aim to highlight the benefits and uses of preference testing, along with potential methods that could be used for preference testing of medical devices. A key step towards the wider implementation of preference testing in medical devices is for the publication of international standards and guidelines for the collection, assessment, and implementation of preference data into the life cycle of a medical device.

Global Landscape of Benefit-Risk Considerations for Medicinal Products: Current State and Future Directions

In the last decade there has been a significant increase in the literature discussing the use of benefit-risk methods in medical product (including devices) development. Government agencies, medical product industry groups, academia, and collaborative consortia have extensively discussed the advantages of structured benefit-risk assessments. However, the abundance of information has not resulted in a consistent way to utilize these findings in medical product development. Guidelines and papers on methods, even though well structured, have not led to a firm consensus on a clear and consistent approach. This paper summarizes the global landscape of benefit-risk considerations for product- or program-level decisions from available literature and regulatory guidance, providing the perspectives of three stakeholder groups-regulators, collaborative groups and consortia, and patients. The paper identifies key themes, potential impact on benefit-risk assessments, and significant future trends.

Benefit-risk assessment and reporting in clinical trials of chronic pain treatments: IMMPACT recommendations

ABSTRACT

Chronic pain clinical trials have historically assessed benefit and risk outcomes separately. However, a growing body of research suggests that a composite metric that accounts for benefit and risk in relation to each other can provide valuable insights into the effects of different treatments. Researchers and regulators have developed a variety of benefit-risk composite metrics, although the extent to which these methods apply to randomized clinical trials (RCTs) of chronic pain has not been evaluated in the published literature. This article was motivated by an Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials consensus meeting and is based on the expert opinion of those who attended. In addition, a review of the benefit-risk assessment tools used in published chronic pain RCTs or highlighted by key professional organizations (ie, Cochrane, European Medicines Agency, Outcome Measures in Rheumatology, and U.S. Food and Drug Administration) was completed. Overall, the review found that benefit-risk metrics are not commonly used in RCTs of chronic pain despite the availability of published methods. A primary recommendation is that composite metrics of benefit-risk should be combined at the level of the individual patient, when possible, in addition to the benefit-risk assessment at the treatment group level. Both levels of analysis (individual and group) can provide valuable insights into the relationship between benefits and risks associated with specific treatments across different patient subpopulations. The systematic assessment of benefit-risk in clinical trials has the potential to enhance the clinical meaningfulness of RCT results.

Making space for patients' preferences in precision medicine: a qualitative study exploring perspectives of patients with rheumatoid arthritis

OBJECTIVE

Precision medicine in rheumatoid arthritis (RA) creates new opportunities to involve patients in early identification of accurate indicators of health trajectories. The aim of this study was to explore patient perspectives on patient-centredness in precision medicine for RA treatment.

DESIGN

Semistructured interviews were conducted to explore patients' perspectives on a new personalised approach to RA treatment. The interview guide was developed together with patient research partners and health care professionals.

SETTING

An invitation to the interviews was sent through a mobile application. The interviews were one-on-one, using an interview guide with open-ended questions. Interviews were conducted digitally (October 2020-February 2021) via Zoom or telephone, depending on each participant's preferences.

PARTICIPANTS

Patients with RA (N=12) were purposively recruited. Patients were eligible if they had an RA diagnosis, were aged 18-80 years, and understood and expressed themselves in Swedish. Participants and researchers did not know each other prior to the interviews.

RESULTS

Participants expressed desires and needs for patients to have an active role in precision medicine by making shared treatment decisions together with a healthcare professional. In order for that to work, patients need information on potential treatment options, an ability to express their preferences, an individual treatment plan and identification of personal treatment goals. Patients also identified two requirements of healthcare professional in precision medicine: a safe environment to express personal matters and two-way communication with healthcare professionals.

CONCLUSION

Communication between patients and healthcare professionals needs to be more focused on patients' individual treatment preferences and expressed needs, in order to increase patient-centredness in treatment decisions, so shared decision-making can become a reality. More research is needed to design multifaceted implementation strategies to support patients and healthcare professionals to increase patient-centredness throughout treatment personalisation.

Inflammatory Bowel Disease Patients' Treatment Preferences Using a Discrete Choice Experiment Technique: The InPuT Study

Introduction

The aim of this study was to investigate patients’ preferences regarding the evolving treatment landscape in Crohn’s disease (CD) and ulcerative colitis (UC) based on a discrete choice experiment.

Methods

Eligible patients (aged 18 years or older) had a confirmed diagnosis of CD or UC and were willing and able to participate in telephone interviews. The survey design is based on a prior literature review, a pilot study, and clinical expert discussions. Preferences related to clinical and practical features of advanced therapies, like tumor necrosis factor alpha inhibitors, anti-integrins, anti-interleukins, and Janus kinase inhibitors, were assessed. Patients were asked to choose between two different hypothetical treatment alternatives visualized in up to 11 choice scenarios. Based on these choices, the relative importance of treatment characteristics was derived from regression coefficients estimated by a conditional logit model.

Results

Of the 291 patients included, 219 (75%) were eligible for this analysis. Among the evaluated attributes in CD, 1-year remission rate was ranked highest, with 42.3% relevance for the overall decision. The second most important attribute was the frequency of serious adverse events (AE) (25.1%), followed by sustained remission over 2 years (17.8%). Lower importance was assigned to the administration mode (14.6%) and none to the frequency of non-serious AE (0.1%). In UC, preferences were driven by efficacy (25.3% for mucosal healing; 23.4% for corticosteroid-free remission) and the frequency of serious AE (18.3%), followed by the administration mode (18.1%). Also, non-serious AE were classified as relevant factors for decision-making (10.7%), while maintaining remission for at least 2 years showed no significant impact (4.4%).

Conclusion

For both indications, efficacy outcomes were rated most important, followed by the frequency of serious AE. Variations were mainly found in the evaluation of non-serious AE and sustained remission. Considering patient preferences may improve the effectiveness of available therapies for moderate to severe CD and UC.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12325-022-02143-z.

Perspectives of at-Risk Individuals on Preventive Intervention for Rheumatoid Arthritis: A Mini Review

There has been intense research focus on the biological mechanisms underlying the transition from health to disease for rheumatoid arthritis (RA) over recent years, and it is now well established that a state of autoimmunity precedes the development of symptoms for a large proportion of patients. This has led to an increased interest in the identification of at-risk groups and the potential for preventive intervention. The ability of several immunomodulatory agents to delay or prevent RA is under investigation and novel cellular therapies are in development. Preventive approaches are also being assessed in other chronic autoimmune diseases. For example, an anti-CD3 antibody has recently been shown to delay progression to type 1 diabetes in non-diabetic relatives of patients identified as being at high risk. The identification and treatment of individuals as being at risk of a disease where there is a degree of uncertainty around the potential for benefit is socially and ethically challenging. Recently reported difficulties in recruitment to RA prevention trials have underlined the importance of understanding the perspectives of at-risk individuals to identify barriers and facilitators that need to be addressed in order for preventive strategies to be acceptable. Understanding of their preferences for benefits and risks of preventive interventions can inform efficient intervention prioritization, prevention trial design and the development of informational resources for those at risk. In this review we summarize current knowledge of preferences for RA prevention and make recommendations for further research needed to ensure efficient development of preventive therapies and clinical implementation.

Examining patient and professional perspectives in the UK for gene therapy in haemophilia

Introduction

With the development of gene therapy for people with haemophilia (PWH), it is important to understand how people impacted by haemophilia (PIH) and clinicians prioritise haemophilia treatment attributes to support informed treatment decisions.

Objective

To examine the treatment attribute preferences of PIH and clinical experts in the United Kingdom (UK) and to develop a profile of gene therapy characteristics fit for use in future discrete choice experiments (DCEs).

Methods

Semi‐structured interviews were conducted with PIH (n = 14) and clinical experts (n = 6) who ranked pre‐defined treatment attributes by importance. Framework analysis was conducted to identify key themes and treatment attributes; points were allocated based on the rankings. Synthesis of results by a multidisciplinary group informed development of a profile of gene therapy characteristics for use in future research.

Results

Key themes identified by PIH and clinical experts included patient relevant features and the importance of ‘informed decision making'. The six top‐ranked treatment attributes were ‘effect on factor level’ (79 points), ‘uncertainty regarding long‐term risks’ (57 points), ‘impact on daily life’ (41 points), ‘frequency of monitoring’ (33 points), ‘impact on ability to participate in physical activity’ (29 points), and ‘uncertainty regarding long‐term benefits’ (28 points). The final treatment characteristics were categorised as therapeutic option, treatment effectiveness, safety concerns, impact on self‐management and quality of life (role limitations).

Conclusion

We identified several gene therapy characteristics important to PIH and clinicians in the UK. These characteristics will be used in a future DCE to further investigate patient preferences for gene therapy.

Multi‐method quantitative benefit‐risk assessment of treatments for moderate‐to‐severe osteoarthritis

Objective

Demonstrate how benefit‐risk profiles of systemic treatments for moderate‐to‐severe osteoarthritis (OA) can be compared using a quantitative approach accounting for patient preference.

Study design and setting

This study used a multimethod benefit‐risk modelling approach to quantifiably compare treatments of moderate‐to‐severe OA. In total four treatments and placebo were compared. Comparisons were based on four attributes identified as most important to patients. Patient Global Assessment of Osteoarthritis was included as a favourable effect. Unfavourable effects, or risks, included opioid dependence, nonfatal myocardial infarction and rapidly progressive OA leading to total joint replacement. Clinical data from randomized clinical trials, a meta‐analysis of opioid dependence and a long‐term study of celecoxib were mapped into value functions and weighted with patient preferences from a discrete choice experiment.

Results

Lower‐dose NGFi had the highest weighted net benefit‐risk score (0.901), followed by higher‐dose NGFi (0.889) and NSAIDs (0.852), and the lowest score was for opioids (0.762). Lower‐dose NGFi was the highest‐ranked treatment option even when assuming a low incidence (0.34% instead of 4.7%) of opioid dependence (ie, opioid benefit‐risk score 808) and accounting for both the uncertainty in clinical effect estimates (first rank probability 46% vs 20% for NSAIDs) and imprecision in patient preference estimates (predicted choice probability 0.26, 95% confidence interval [CI] 0.25‐0.28 vs 0.21, 95% CI 0.19‐0.23 for NSAIDs).

Conclusion

The multimethod approach to quantitative benefit‐risk modelling allowed the interpretation of clinical data from the patient perspective while accounting for uncertainties in the clinical effect estimates and imprecision in patient preferences.

Patient Preference for Biologic Treatments of Psoriasis in the Chinese Setting

OBJECTIVE

Assessments of patients' preferences can support in clinical decision-making regarding biologic therapies for psoriasis. Our objective was to investigate patient preference for biologic treatments in patients with psoriasis in China.

METHODS

From October 2020 to January 2021, psoriasis patients were recruited for a survey that included demographic and disease-related questions, as well as a discrete choice experiment to measure their preferences for biologic therapy. A discrete-choice experiment was used in which respondents selected psoriasis treatments based on benefits (ie, early onset of efficacy, long-term efficacy, sustained efficacy) and treatment costs. We analyzed choice data using conditional logit model.

RESULTS

This study included 236 patients with moderate-to-severe psoriasis. The relative importance of the cost of biologic treatments, probability of keeping PASI100 at 5 years, probability of achieving PASI100 at 3 months and time to achieve PASI50 after initiation the biologic treatment were 0.593, 0.137, 0.185 and 0.085. Over 50% of patients regarded the cost of biologic treatments as the most important attribute. High-income and low-income subgroups had higher preference weight in probability of achieving PASI100 at 3-month and monthly cost.

CONCLUSION

The cost of biologic treatments was found as the most important attribute for Chinese patients with psoriasis. Among efficacy attributes, the probability of achieving PASI100 at 3 months showed most sensitive. These results may be helpful to understand patient preference for biologic treatments used for psoriasis in China.

Patient Preference Studies for Advanced Prostate Cancer Treatment Along the Medical Product Life Cycle: Systematic Literature Review

BACKGROUND

Patient preference studies can inform decision-making across all stages of the medical product life cycle (MPLC). The treatment landscape for advanced prostate cancer (APC) treatment has substantially changed in recent years. However, the most patient-relevant aspects of APC treatment remain unclear. This systematic review of patient preference studies in APC aimed to summarize the evidence on patient preferences and patient-relevant aspects of APC treatments, and to evaluate the potential contribution of existing studies to decision-making within the respective stages of the MPLC.

METHODS

We searched MEDLINE and EMBASE for studies evaluating patient preferences related to APC treatment up to October 2020. Two reviewers independently performed screening, data extraction and quality assessment in duplicate. We descriptively summarized the findings and analyzed the studies regarding their contribution within the MPLC using an analytical framework.

RESULTS

Seven quantitative preference studies were included. One study each was conducted in the marketing approval and the health technology assessment (HTA) and reimbursement stage, and five were conducted in the post-marketing stage of the MPLC. While almost all stated to inform clinical practice, the specific contributions to clinical decision-making remained unclear for almost all studies. Evaluated attributes related to benefits, harms, and other treatment-related aspects and their relative importance varied relevantly between studies. All studies were judged of high quality overall, but some methodological issues regarding sample selection and the definition of patient-relevant treatment attributes were identified.

CONCLUSION

The most patient-relevant aspects regarding the benefits and harms of APC treatment are not yet established, and it remains unclear which APC treatments are preferred by patients. Findings from this study highlight the importance of transparent reporting and discussion of study findings according to their aims and with respect to their stage within the MPLC. Future research may benefit from using the MPLC framework for analyzing or determining the aims and design of patient preference studies.

Net clinical benefit of antiplatelet therapy was affected by patient preferences: A personalized benefit-risk assessment

OBJECTIVE

To assess the effect of patient preferences on the net clinical benefit (NCB) of an antiplatelet therapy for the secondary prevention of cardiovascular complications.

STUDY DESIGN AND SETTING

Risk equations were developed to estimate the individual predicted risk of key outcomes of antiplatelet treatment in patients with a prior myocardial infarction using the Clinical Practice Research Datalink linked to the Hospital Episode Statistics and UK Office of National Statistics databases. Patient preferences for outcomes of antiplatelet therapies were elicited in a separate discrete choice experiment survey. Trial hazard ratios, relative to placebo, were used to calculate the per-patient NCB using equal or preference weighting of outcomes.

RESULTS

Risk equations were estimated using 31,941 adults in the Clinical Practice Research Datalink population, of which 22,125 were included in the benefit-risk assessment. The mean NCB was lower in the preference-weighted than in the equal-weighted analysis (0.040 vs 0.057; p < 0.0001), but the direction of effect was unchanged by the weighting. In analyses stratified by the presence of bleeding risk factors, including preference weighting altered the ranking of subgroups by NCB.

CONCLUSION

Patient preference weighting may have a significant effect on NCB and should be included in personalized benefit-risk assessments.

Assessing Patient Preferences in Rare Diseases: Direct Preference Elicitation in the Rare Chronic Kidney Disease, Immunoglobulin A Nephropathy

Background

Patient preference information is increasingly being used to inform decision making; however, further work is required to support the collection of preference information in rare diseases. This study illustrates the use of direct preference elicitation methods to collect preference data from small samples in the context of early decision making to inform the development of a product for the treatment of immunoglobulin A nephropathy.

Method

An interview-based swing weighting approach was used to elicit preferences from 40 patients in the US and China. Attributes were identified through a background review, expert engagement and patient focus groups. Participants completed a series of tasks that involved ranking, rating and scoring improvements in the attributes to obtain attribute swing weights and partial value functions. The preference results were then incorporated into a benefit-risk assessment simulation tool.

Results

Participants placed the greatest value on avoiding end-stage renal/kidney disease. Similar weight was given to short-term quality-of-life improvements and avoiding infections. Treatment burden (number of vaccinations) received the least weight. Heterogeneity in preferences was also observed. Consistency tests did not identify statistically significant variation in preferences, and qualitative data suggested that the elicitation exercise was sensitive to participants’ interpretation of attributes and that participants were able to express their preferences.

Conclusion

Direct preference elicitation methods can be used to collect preference data from small samples. Further work should continue to test the validity of the estimate generated by such methods.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40271-021-00521-3.

Functional capacity vs side effects: treatment attributes to consider when individualising treatment for patients with rheumatoid arthritis

Introduction

Individualisation of rheumatoid arthritis (RA) treatment needs to take account of individual patients’ preferences to increase patient-centeredness in treatment decisions. The aim of this study was to identify patient-relevant treatment attributes to consider when individualising treatment for patients with RA.

Method

Patients with RA in Sweden were invited to rank the most important treatment attributes in an online survey (April to May 2020). Semi-structured interviews were conducted (October to November 2020) to further identify and frame potential attributes for shared decision-making. The interviews were audio-recorded, transcribed and analysed using thematic framework analysis. Patient research partners and rheumatologists supported the selection and framing of the treatment attributes across the assessment.

Results

The highest ranked attributes (N = 184) were improved functional capacity, reduced inflammation, reduced pain and fatigue and the risk of getting a severe side effect. The framework analysis revealed two overarching themes for further exploration: treatment goals and side effects. ‘Treatment goals’ emerged from functional capacity, revealing two dimensions: physical functional capacity and psychosocial functional capacity. ‘Side effects’ revealed that mild and severe side effects were the most important to discuss in shared decision-making.

Conclusions

Functional capacity (physical and psychosocial) and potential side effects (mild and severe) are important treatment attributes to consider when individualising RA treatment. Future research should assess how patients with RA weigh benefits and risks against each other, in order to increase patient-centeredness early on the treatment trajectory.

Clarifying Values: An Updated and Expanded Systematic Review and Meta-Analysis

Background

Patient decision aids should help people make evidence-informed decisions aligned with their values. There is limited guidance about how to achieve such alignment.

Purpose

To describe the range of values clarification methods available to patient decision aid developers, synthesize evidence regarding their relative merits, and foster collection of evidence by offering researchers a proposed set of outcomes to report when evaluating the effects of values clarification methods.

Data Sources

MEDLINE, EMBASE, PubMed, Web of Science, the Cochrane Library, and CINAHL.

Study Selection

We included articles that described randomized trials of 1 or more explicit values clarification methods. From 30,648 records screened, we identified 33 articles describing trials of 43 values clarification methods.

Data Extraction

Two independent reviewers extracted details about each values clarification method and its evaluation.

Data Synthesis

Compared to control conditions or to implicit values clarification methods, explicit values clarification methods decreased the frequency of values-incongruent choices (risk difference, –0.04; 95% confidence interval [CI], –0.06 to –0.02; P < 0.001) and decisional conflict (standardized mean difference, –0.20; 95% CI, –0.29 to –0.11; P < 0.001). Multicriteria decision analysis led to more values-congruent decisions than other values clarification methods (χ² = 9.25, P = 0.01). There were no differences between different values clarification methods regarding decisional conflict (χ² = 6.08, P = 0.05).

Limitations

Some meta-analyses had high heterogeneity. We grouped values clarification methods into broad categories.

Conclusions

Current evidence suggests patient decision aids should include an explicit values clarification method. Developers may wish to specifically consider multicriteria decision analysis. Future evaluations of values clarification methods should report their effects on decisional conflict, decisions made, values congruence, and decisional regret.

Patient Preferences in Rare Diseases: A Qualitative Study in Neuromuscular Disorders to Inform a Quantitative Preference Study

INTRODUCTION

It has become increasingly important to include patient preference information in decision-making processes for drug development. As neuromuscular disorders represent multisystem, debilitating, and progressive rare diseases with few treatment options, this study aimed to explore unmet health care needs and patient treatment preferences for two neuromuscular disorders, myotonic dystrophy type 1 (DM1) and mitochondrial myopathies (MM) to inform early stages of drug development.

METHODS

Fifteen semi-structured interviews and five focus group discussions (FGDs) were held with DM1 and MM adult patients and caregivers. Topics discussed included (1) reasons for study participation; (2) disease signs/symptoms and their impact on daily lives; (3) top desired benefits; and (4) acceptability of risks and tolerance levels for a hypothetical new treatment. Data were analyzed following a thematic 'code' approach.

RESULTS

A total of 52 participants representing a wide range of disease severities participated. 'Muscle strength' and 'energy and endurance' were the disease-related unmet needs most often mentioned. Additionally, improved 'balance', 'cognition' and 'gut function' were the top desired treatment benefits, while 'damage to the liver, kidneys or eyes' was the most concerning risk. Factors influencing their tolerance to risks related to previously having experienced the risk and differentiation between permanent and temporary risks. A few differences were elicited between patients and caregivers.

CONCLUSIONS

This qualitative study provided an open forum to elicit treatment-desired benefits and acceptable risks to be established by patients themselves. These findings can inform decisions for developing new treatments and the design of clinical trials for DM1 and MM.

Patient-reported benefits of bone-anchored transfemoral prostheses as assessed by MedTech20: A general outcome measure for medical products

BACKGROUND

The medical community demands evidence for the benefits of medical devices such as bone-anchored prostheses (BAPs). MedTech20  is a novel instrument aiming to address general benefits of medical devices.

OBJECTIVE

To describe general patient-reported benefits of BAPs measured with MedTech20.

STUDY DESIGN

This is a cross-sectional descriptive survey.

METHODS

Patients treated in Sweden who had used a BAP for >1 year were mailed the MedTech20  Questionnaire. Responses to each attribute were described, and the MedTech20   Index (0-1), in which a higher figure represents larger benefits from the product, was calculated. Index values were compared based on demographic variables (sex, unilateral or bilateral transfemoral amputation (TFA), and those having experienced any complication of implant parts or the prosthetic connection device).

RESULTS

The response rate was 72%. The 62 participants (41 men and 21 women; mean age 57 years) had 11 ± 6.9 mean years of BAP experience. Single attributes stated as highly relevant and with high benefit for BAPs included perceived reliability, perceived safety, sense of control of the disability, facilitation of movement outside home, no discomfort at use, and ease of use. Attributes with less relevance included aid to remember tasks, reduction of barriers to a good sleep, and reduced sense of compromised integrity. The MedTech20  Index was 0.655 ± 0.188 and was not statistically significantly different based on any of the demographic variables.

CONCLUSIONS

By using a general measure on attributes of medical devices, this study provides new insights strengthening the evidence regarding the benefits that BAPs provide for patients with TFA who had difficulties with socket-suspended prostheses.

An implantable device to treat multiple sclerosis: A discrete choice experiment on patient preferences in three European countries

BACKGROUND

Persons with multiple sclerosis (MS) take their treatment via pills, injections or infusions. A novel mode of disease-modifying treatment administration, an implantable device, is under development. This study determined MS patient preferences for three modes of first-line treatment administration (implant, pills, injectables), and trade-offs regarding treatment characteristics.

METHODS

A survey including a discrete choice experiment was conducted among MS patients in the Netherlands, France, and the United Kingdom. Respondents had to repeatedly choose between various treatment scenarios with four treatment characteristics: risk of relapse, reduction of disease progression, risk of side effects and mode of administration. Data was analysed using a panel latent class logit model.

RESULTS

Based on the preferences of 753 MS patients (response rate 7%: 753/11202), two latent classes were identified (class probability of 74% vs 26%). Persons with relapsing-remitting MS and who administered medication via injections generally preferred any treatment over no treatment. Patients who could walk without an aid were more likely to prefer no treatment. Reducing disease progression was the most important treatment characteristic class 1. Mode of administration was the most important characteristic in class 2. Patients were willing to accept an increase in risk of relapse and disease progression to get their treatment via an implant rather than injections. Predicted uptake was the highest for the implant, followed by pills, injections, and no treatment.

CONCLUSION

We found that a drug-delivery implant could be a potential addition to the MS treatment landscape: MS patients are willing to trade-off risk of relapse and disease progression for an implant, and predicted uptake for an implant is relatively high.