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Development of clear and effective discrete-choice experiment surveys is an important step toward ensuring accurate and usable preference results. Pretest interviews and pilot testing are common in the development of discrete-choice experiments, and it is important for researchers to report details of survey changes resulting from patient feedback elicited in pilot work. This paper details pilot testing of an online discrete-choice experiment to elicit preferences for long-acting antiretroviral therapies among patients with HIV.The survey included an introduction to hypothetical treatment options, descriptions of attributes, comprehension questions, instructions for completing a discrete-choice experiment, a discrete-choice experiment with 17 choice tasks, and questions about personal characteristics. We piloted the survey with 50 respondents over ten waves. Each wave incorporated design improvements based on observations made during the previous wave. Respondents completed the online survey while screen sharing with a researcher, allowing interactive discussion. We developed a scheme for assessing and categorizing the survey changes.Changes to the pilot were categorized by ways they impacted aspects of the discrete-choice experiment or the likely quality of resulting data. The four categories of impact are: understanding of attributes, underlying discrete-choice experiment and understanding of the choice question, collection of individual characteristics hypothesized to affect preference, and changes that improved clarity and usability of the survey without directly affecting the other categories (e.g., survey navigation and instructional clarity, formatting changes).Detailed attention to the respondent experience in this large pilot allowed survey improvements that will likely reduce ambiguity, ensure more accurate capture of patient preferences and, ultimately, improve product development for long-acting antiretroviral therapies.

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.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.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.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.

To rank the US payers' preferences for attributes of real-world evidence (RWE) studies in the context of chronic disease and to quantify trade-offs among them.We conducted a discrete choice experiment in which 180 employees from payer organizations were tasked to choose between 2 RWE studies assuming they were assessing evidence to inform formulary decisions for chronic disease treatment. Each RWE study was characterized by 7 attributes with 3 levels each: very informative, moderately informative, and not measured. We used a D-optimal main-effects design. Survey data were fitted to a conditional logit model to obtain a relative measure of the ranking of importance for each attribute.Clinical outcomes were the most preferred attribute. It was 4.68 times as important as productivity outcomes-the least preferred attribute. It was followed by health-related quality of life (2.78), methodologic rigor (2.09), resource utilization (1.71), and external validity (1.56).This study provides a quantification of the value payers place on key RWE attributes. Across attributes, payers have higher preferences for clinical and health-related quality of life outcomes than the other attributes. Between attributes' levels, payers prefer high levels of information in clinical outcomes and methodologic rigor but are indifferent in other attributes. Our results bridge the gap between the information that payers seek and the attributes that RWE studies prioritize and effectively guide future research design.

Lay abstract CAR-T therapy is a treatment option for patients with diffuse large B-cell lymphoma that has not responded to at least two other kinds of treatments. CAR-T therapies are manufactured from a patient’s white blood cells, modified to attack lymphoma cells. A CAR-T therapy takes time to manufacture after these cells are collected. CAR-T therapies can result in the reduction or disappearance of lymphoma tumors and can increase the chances of survival, but also cause serious side effects for a few patients. One of these is cytokine release syndrome (CRS), in which high levels of inflammation throughout the body may cause fever, heart problems or difficulty breathing. Another is the development of temporary but serious neurological problems such as confusion, seizures and memory problems. To understand how important physicians consider certain features of CAR-T therapies to be when deciding whether to recommend them, we asked physicians to choose between two treatment options resembling CAR-T therapies in a series of questions, with the CAR-T features varying in each question. Their answers indicated whether disappearance of tumors, a patient’s chances of survival after 1 and 2 years of treatment, manufacturing time, or the risk of CRS or neurological problems was the most important factor. Physicians most wanted to reduce manufacturing time from 113 to 16 days, but also were willing to accept a20% increase in risk of severe CRS and a 15% increase in risk of severe neurological events to increase a patient’s chance of survival from 40 to 55% at 2 years.

Background Health checks can detect risk factors and initiate prevention of cardiovascular diseases but there is no consensus on how to communicate the results. The aim of this study was to investigate the preferences of the general population for communicating health check results. Methods A randomly selected sample of the Swedish population aged 40–70 years completed a discrete choice experiment survey that included questions on sociodemographics, lifestyle and health and 15 choice questions consisting of six attributes (written results, notification method, consultation time, waiting time, lifestyle recommendation and cost). Data were analyzed with a latent class analysis (LCA). Relative importance of the attributes and predicted uptake for several scenarios were estimated. Results In the analysis, 432 individuals were included (response rate 29.6%). A three-class LCA model best fit the data. Cost was the most important attribute in all classes. Preferences heterogeneity was found for the other attributes; in Class 1, receiving consultation time and the written results were important, respondents in Class 2 dominated on costs and respondents in Class 3 found consultation time, waiting time and lifestyle recommendations to be important. Health literate respondents were more likely to belong to Class 3. The predicted uptake rates ranged from 7 to 88% for different health checks with large differences across the classes. Conclusion Cost was most important when deciding whether to participate in a health check. Although cost was the most important factor, it is not sufficient to offer health checks free-of-charge if other requirements regarding how the test results are communicated are not in place; participants need to be able to understand their results. Supplementary Information The online version contains supplementary material available at 10.1007/s40271-021-00512-4.

Background The patient ranking process for donor lung allocation in the United States is carried out by a classification-based, computerized algorithm, known as the match system. Experts have suggested that a continuous, points-based allocation framework would better serve waiting list candidates by removing hard boundaries and increasing transparency into the relative importance of factors used to prioritize candidates. We applied discrete choice modeling to match run data to determine the feasibility of approximating current lung allocation policy by one or more composite scores. Our study aimed to demystify the points-based approach to organ allocation policy; quantify the relative importance of factors used in current policy; and provide a viable policy option that adapts the current, classification-based system to the continuous allocation framework. Methods Rank ordered logistic regression models were estimated using 6466 match runs for 5913 adult donors and 534 match runs for 488 pediatric donors from 2018. Four primary attributes are used to rank candidates and were included in the models: (1) medical priority, (2) candidate age, (3) candidate’s transplant center proximity to the donor hospital, and (4) blood type compatibility with the donor. Results Two composite scores were developed, one for adult and one for pediatric donor allocation. Candidate rankings based on the composite scores were highly correlated with current policy rankings (Kendall’s Tau ~ 0.80, Spearman correlation > 90%), indicating both scores strongly reflect current policy. In both models, candidates are ranked higher if they have higher medical priority, are registered at a transplant center closer to the donor hospital, or have an identical blood type to the donor. Proximity was the most important attribute. Under a points-based scoring system, candidates in further away zones are sometimes ranked higher than more proximal candidates compared to current policy. Conclusions Revealed preference analysis of lung allocation match runs produced composite scores that capture the essence of current policy while removing rigid boundaries of the current classification-based system. A carefully crafted, continuous version of lung allocation policy has the potential to make better use of the limited supply of donor lungs in a manner consistent with the priorities of the transplant community.

Objectives: To identify meaningful treatment attributes and quantify patient preferences for attributes of systemic atopic dermatitis (AD) treatments. Materials and methods: Qualitative interviews were conducted with adults with moderate-to-severe AD (N = 21) to identify AD treatment attributes that patients consider most important and inform attribute selection for an online discrete-choice experiment (DCE) survey administered to patients in the United States with moderate-to-severe AD. Participants identified probability of clear/almost clear skin at 16 weeks, time to itch relief, mode of administration, and safety risks as very important. DCE data were analyzed using a random-parameters logit model to estimate the relative importance of treatment attributes and maximum acceptable risk. Results: A total of 320 respondents completed the DCE survey (74% female; mean age, 35 years). Annual risk of malignancy was the most important attribute, followed by mode of administration, probability of clear skin at 16 weeks, and time to onset of itch relief. Respondents preferred daily oral treatment over injectable treatment. Respondents were willing to accept increases in adverse event risks for improvements in efficacy and mode of administration. Conclusion: The findings of this study can help inform joint patient-physician decision making in managing moderate-to-severe AD.

Background Benefit–risk assessments for medicinal products and devices have advanced significantly over the past decade. The purpose of this study was to characterize the extent to which the life sciences industry is utilizing quantitative benefit–risk assessment (qBRA) methods. Methods Semi-structured interviews were conducted with a sample of industry professionals working in drug and/or medical device benefit–risk assessments (n = 20). Questions focused on the use, timing, and impact of qBRA; implementation challenges; and future plans. Interviews were recorded, transcribed, and coded for thematic analysis. Results While most surveyed companies had applied qBRA, application was limited to a small number of assets—primarily to support internal decision-making and regulatory submissions. Positive impacts associated with use included improved team decision-making and communication. Multi-criteria decision analysis and discrete choice experiment were the most frequently utilized qBRA methods. A key challenge of qBRA use was the lack of clarity regarding its value proposition. Championing by senior company leadership and receptivity of regulators to such analyses were cited as important catalysts for successful adoption of qBRA. Investment in qBRA methods, via capability building and pilot studies, was also under way in some instances. Conclusion qBRA application within this sample of life sciences companies was widespread, but concentrated in a small fraction of assets. Its use was primarily for internal decision-making or regulatory submissions. While some companies had plans to build further capacity in this area, others were waiting for further regulatory guidance before doing so.

Purpose Immuno-oncology treatments offer patients with advanced non-small cell lung cancer (NSCLC) treatment options with greater probability of durable survival and a different toxicity profile compared with traditional chemotherapy. The objective of this study was to explore the importance of increases in the probability of long-term survival versus changes in expected (median) survival and treatment toxicities among patients with advanced NSCLC and physicians. Patients and methods In a discrete-choice experiment, oncologists and patients diagnosed with NSCLC chose between profiles of treatments for advanced NSCLC offering different combinations of benefits (expected, best-case, and worst-case survival) and risks. We analyzed preference data from each sample using a random-parameters logit model that controls for preference heterogeneity and the panel nature of the data. Results Both patients and physicians expressed a strong preference for improving the probability of best-case survival; however, patients viewed increases in the probability of long-term survival as more important than increases in expected survival, while the opposite was true for physicians. Both patients and physicians weighted survival to be more important than toxicities. Conclusion This study identified a potentially important divergence between physician and patient perspectives on survival statistics. Physicians placed more importance on increases in expected survival than did patients with NSCLC. The importance patients placed on long-term survival reinforce previous research identifying the primacy of hope as a value among seriously ill patients. The findings underscore the importance of considering patients' priorities and in shared decision-making when choosing treatment.

Background The What Matters Most (WMM) study was initiated to evaluate symptoms, AD-related impacts, treatment-related needs, preferences, and priorities among individuals with or at risk for Alzheimer’s disease (AD) and their care partners. The objective of this qualitative study phase was to identify a comprehensive set of concepts of interest that are meaningful to individuals across the AD continuum. Methods Interviews were conducted with 60 clinically referred individuals and care partners across 5 AD stages (n = 12 each): group 1 (non-clinically impaired individuals with AD pathology), group 2 (individuals with mild cognitive impairment and AD pathology), group 3 (individuals with mild AD), group 4 (individuals with moderate AD and their care partners), and group 5 (care partners of individuals with severe AD). Interviews were conducted by experienced interviewers, audio-recorded, and transcribed. Dominant trends were identified in each interview and compared across subsequent interviews to generate themes or patterns in descriptions of AD symptoms, impacts, and desired treatment outcomes. Results All participants endorsed current issues related to memory; nearly all participants (n = 55; 92%) across the five groups endorsed symptoms related to communication and language. Groups 1–3 reported an impact on mood/emotions (n = 23; 64%) and a decrease in social activities or outgoingness (n = 17; 47%). Current and future concerns reported by the overall sample included memory (n = 48; 80%), dependence (n = 40; 67%), and “other” concerns (n = 33; 55.0%) (e.g., uncertainty about the future, burdening others). The most desired AD treatment outcomes were improvement or restoration of memory (n = 40; 67%) and stopping AD progression (n = 35; 58.3%). Group-level differences were observed in the symptoms, impacts, and desired treatment outcomes among patients and care partners across the AD continuum. Conclusions Cognitive functioning issues—particularly in memory and communication—are present even in preclinical and early-stage AD, including among those without a formal AD diagnosis. While the impacts of AD vary across the disease-severity spectrum, improved memory and disease modification were treatment outcomes considered most important to participants across all 5 AD stages. Neuropsychological assessments traditionally used in AD clinical trials may not evaluate the often-subtle concepts that are important to patients and care partners. Results from this study will inform the second phase of the WMM project—a quantitative study to elicit the relative importance of these concepts of interest to people at risk for and living with AD and their care partners.

Purpose Teriparatide is used to treat patients with established osteoporosis but is often reserved for patients who have inadequate response to antiresorptive therapy. Biosimilar teriparatide, which is believed to have efficacy and safety similar to the originator product, is now available in Colombia. However, little is known about patients' preferences for originator biologic and biosimilar treatments. Our objective was to quantify the relative importance that patients in Colombia place on features of injectable osteoporosis treatments including whether the treatment is an originator biologic or a biosimilar. Patients and methods We used a discrete choice experiment (DCE) to elicit preferences of patients with osteoporosis treatment devices in Colombia. The survey was completed by 200 respondents at high risk of fracture, with or without teriparatide experience. Each treatment alternative within the DCE was characterized by five attributes: type of medicine (originator biologic, biosimilar), needle length, angle of injection, how to measure the medicine dose, and how long the medicine can be left unrefrigerated. A random parameters logit regression was used to estimate preferences and conditional relative attribute importance, while controlling for preference heterogeneity. Results A total of 200 patients (mean age = 58.3 years) completed the survey. Most were female (84.5%) and married (54.5%); 50.5% had secondary education or less, 21% had current teriparatide exposure. The attribute with the highest conditional relative importance estimate (standard error) was biologic versus biosimilar (10 [1.11]), followed by needle length (8.06 [1.11]), dose measurement (6.38 [0.87]), refrigeration (3.81 [1.18]), and angle of injection (1.30 [0.66]). Unobserved preference heterogeneity was present and controlled for in the analyses. Conclusion Despite the availability of biosimilar teriparatide in Colombia, patients expressed a strong preference for an originator biologic osteoporosis medicine over a biosimilar osteoporosis medicine, when the efficacy, safety, and cost of the two options were assumed to be the same.

Either a random-parameters logit (RPL) or latent class (LC) model can be used to model or explain preference heterogeneity in discrete-choice experiment (DCE) data. The former assumes continuous distribution of preferences across the sample, while the latter assumes a discrete distribution. This study compared RPL and LC models to explore preference heterogeneity when analyzing patient preferences for psoriasis treatments. Using DCE data collected from respondents with moderate-to-severe plaque psoriasis, we calculated and compared preference weights derived from RPL and LC models. We then compared how RPL and LC explain preference heterogeneity by exploring differences across subgroups defined by observed characteristics (i.e., country, age, gender, marital status, and psoriasis severity). While RPL and LC models resulted in the same mean preference weights, different preference-heterogeneity patterns emerged from the two approaches. In both models, country of residence and self-reported disease severity could be linked to systematic differences in preferences. The RPL also identified gender and marital status, but not age, as sources of heterogeneity; the LC membership probability model indicated that age was a significant factor, but not gender or marital status. Using data from a psoriasis patient survey to compare two widely used methods for exploring heterogeneity identified differences in results between stated-preferences: subgroup analysis in the RPL model and inclusion of subgroup characteristics in the class membership probability function of the LC model. Researchers should model data using the most adaptable approach to address the initial study question.

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.

This technical note discusses how dummy and effects coding of categorical respondent characteristics in a class membership probability function should be interpreted by researchers employing a latent class analysis to explore preference heterogeneity in a discrete-choice experiment. Previous work highlighted issues arising from such coding when interpreting an alternative specific constant that represents an opt-out alternative or current situation in a discrete-choice experiment and did not fully address how this coding impacts the interpretation of parameters resulting from the membership probability function in a latent class analysis. Although latent class membership probability could be predicted separately for each respondent or subgroup of respondents, conclusions are often drawn directly from the model estimation using the full sample, which requires correctly interpreting the estimated parameters. In these cases, the misinterpretation that may arise if the problem is ignored could impact the policy conclusions and recommendations drawn based on the discrete-choice experiment results. This note provides an example comparing dummy and effects coding used to model respondent characteristics in the membership probability function in a discrete-choice experiment aimed to explore preferences for the treatment of chronic pain in the USA.

Background: Several pharmaceutical treatments for chronic pain caused by osteoarthritis (OA) and chronic low back pain (CLBP) are available or currently under development, each associated with different adverse events (AEs) and efficacy profiles. It is therefore important to understand what trade-offs patients are willing to make when choosing between treatments. Methods: A discrete-choice experiment (DCE) was conducted with 437 adults with chronic pain caused by OA and/or CLBP. Respondents were presented with a series of scenarios and asked to choose between pairs of hypothetical treatments, each defined by six attributes: level of symptom control; risks of heart attack, rapidly progressive osteoarthritis and dependency; frequency and mode of administration and cost. Attributes were based on known profiles of oral nonsteroidal anti-inflammatory drugs, opioids and injected nerve growth factor inhibitors, the last of which were under clinical development at the time of the study. Data were analysed using a latent class (LC) model to explore preference heterogeneity. Results: Overall, respondents considered improving symptom control and reducing risk of physical dependency to be the most important attributes. The LC analysis identified four participant classes: an ‘efficacy-focused’ class (33.7%), a ‘cost-averse’ class (29.4%), a ‘physical-dependence–averse’ class (19.6%) and a ‘needle-averse’ class (17.3%). Subgroup membership was incompletely predicted by participant age and their responses to comprehension questions. Conclusions: Preference heterogeneity across respondents indicates a need for a personalized approach to offering treatment options. Symptom improvement, cost, physical dependence and route of administration might be important to different patients. Significance: Multiple treatment options that differ substantially in terms of efficacy and adverse events are available for the management of chronic pain. With a growing emphasis on a patient-centred care model that incorporates patients’ priorities and values into treatment decisions, there is a need to understand how individuals with chronic musculoskeletal pain balance the benefits and risks of treatment and how treatment priorities vary among individuals. This study was designed to identify patient preferences for different characteristics of treatments for the management of chronic pain and to investigate how preferences differ among respondents.

Introduction Patient preferences for long-acting antiretroviral therapies (LA-ART) should inform development of regimens with optimal adherence and acceptability. We describe a systematic process used to identify attributes and levels for a discrete choice experiment (DCE) designed to elicit preferences for potential LA-ART options in the US. Methods Our approach was conducted in four stages: data collection, data reduction, removing inappropriate attributes, and optimizing wording. We started with 8 attributes defining potential LA-ART products based on existing literature and knowledge of products in development. We conducted 12 key informant interviews with experts in HIV treatment. The list of attributes, the set of plausible levels for each attribute, and restrictions on combinations of attribute levels were updated iteratively. Results Despite uncertainty about which products will become available, key informant discussions converged on 4 delivery modes (infusions and patches were not considered immediately feasible) and 6 additional attributes. Treatment effectiveness and frequency of clinical monitoring were dropped. Oral lead-in therapy was split into two attributes: pre-treatment time undetectable and pre-treatment negative reaction testing. We omitted product-specific systemic and local side effects. In addition to mode, the final set of attributes included: frequency of dosing; location of treatment; pain; pre-treatment time undetectable; pre-treatment negative reaction testing; and late-dose leeway. Conclusions A systematic process successfully captured elements that are both feasible and relevant to evaluating the acceptability of potential LA-ART alternatives to patients.

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.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.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).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.

Objective To quantify preferences for preventive therapies for rheumatoid arthritis (RA) across three countries. Methods A web-based survey including a discrete choice experiment was administered to adults recruited via survey panels in the UK, Germany and Romania. Participants were asked to assume they were experiencing arthralgia and had a 60% chance of developing RA in the next 2 years and completed 15 choices between no treatment and two hypothetical preventive treatments. Treatments were defined by six attributes (effectiveness, risks and frequency/route of administration) with varying levels. Participants also completed a choice task with fixed profiles reflecting subjective estimates of candidate preventive treatments. Latent class models (LCMs) were conducted and the relative importance of attributes, benefit–risk trade-offs and predicted treatment uptake was subsequently calculated. Results Completed surveys from 2959 participants were included in the analysis. Most participants preferred treatment over no treatment and valued treatment effectiveness to reduce risk more than other attributes. A five-class LCM best fitted the data. Country, perceived risk of RA, health literacy and numeracy predicted class membership probability. Overall, the maximum acceptable risk for a 40% reduction in the chance of getting RA (60% to 20%) was 21.7%, 19.1% and 2.2% for mild side effects, serious infection and serious side effects, respectively. Predicted uptake of profiles reflecting candidate prevention therapies differed across classes. Conclusion Effective preventive pharmacological treatments for RA were acceptable to most participants. The relative importance of treatment attributes and likely uptake of fixed treatment profiles were predicted by participant characteristics.

94 Background: Androgen deprivation therapies (ADTs) for prostate cancer (PC) vary in delivery mode, T (testosterone) surge occurrence, time to T recovery, adverse event profile, and costs. Data are limited on how men differ in their evaluation of ADT attributes. This study identified subgroups of men who vary in their preferences for key ADT attributes. Methods: A cross-sectional survey of US men aged >40 years, who had healthcare coverage for the past 3 years and self-reported a PC diagnosis, were recruited via healthcare research panels. Men were ineligible if they did not know/recall whether they had received ADT or were unable to complete the survey independently. Quotas ensured an approximate even split of ADT-experienced and ADT-naïve men. A discrete choice experiment assessed preferences for ADT attributes. In a series of choice tasks, men were presented with 2 ADT treatment profiles side-by-side and asked to select the one they prefer. Hierarchical Bayes models computed attribute level preference weights. Relative importance (RI), based on differences between the most and least favorable attribute level preference weight and standardized to sum to 100%, was estimated for each attribute; the higher the RI value, the more influential an attribute is to treatment choice. Latent class analysis (LCA) identified groups (Gs) of men with similar ADT preferences. Results: 304 men were included in the analyses, their mean age was 64.4±7.2 years, and 16.8% were African American. Mean PC duration was 5.4±4.8 years, 55.3% reported organ-confined PC, and 49.0% had prior ADT use. LCA identified 4 preference Gs. While impact on sexual activity was most important to G1, out-of-pocket (OOP) costs, mode of administration, and time to T recovery were choice drivers for G2. Mode of administration and OOP costs predominated in importance for G3 and G4, respectively. More than half of men in G1 and G3 were

ObjectivesTo quantify tolerance to risks of preventive treatments among first-degree relatives (FDRs) of patients with rheumatoid arthritis (RA).MethodsPreventive treatments for RA are under investigation. In a preference survey, adult FDRs assumed a 60% chance of developing RA within 2 years and made choices between no treatment and hypothetical preventive treatment options with a fixed level of benefit (reduction in chance of developing RA from 60% to 20%) and varying levels of risks. Using a probabilistic threshold technique, each risk was increased or decreased until participants switched their choice. Perceived risk of RA, health literacy, numeracy, Brief Illness Perception Questionnaire and Beliefs about Medicines Questionnaire-General were also assessed. Maximum acceptable risk (MAR) was summarised using descriptive statistics. Associations between MARs and participants’ characteristics were assessed using interval regression with effects coding.Results289 FDRs (80 male) responded. The mean MAR for a 40% reduction in chance of developing RA was 29.08% risk of mild side effects, 9.09% risk of serious infection and 0.85% risk of a serious side effect. Participants aged over 60 years were less tolerant of serious infection risk (mean MAR ±2.06%) than younger participants. Risk of mild side effects was less acceptable to participants who perceived higher likelihood of developing RA (mean MAR ±3.34%) and more acceptable to those believing that if they developed RA it would last for a long time (mean MAR ±4.44%).ConclusionsAge, perceived chance of developing RA and perceived duration of RA were associated with tolerance to some risks of preventive RA therapy.

IntroductionTo assess convergent validity of stated preference methods in studies where they were used to elicit patient preferences for informing medical product decisions.MethodsIn four studies, two stated preference methods were used to elicit preferences of patients with neuromuscular diseases (NMD; n = 140, Discrete Choice Experiment [DCE] and Best-Worst Scaling [BWS] case 2), diabetes (n = 495, DCE and swing weighting [SW]), myocardial infarction (MI; n = 335, DCE and BWS case 1), and rheumatoid arthritis (RA; n = 982, DCE and probabilistic threshold technique [PTT]). In each study, results of the two methods were compared using a normalized preference measure for which confidence intervals (CIs) were estimated using nonparametric bootstrapping of 500 samples. Normalized preference measures comprised of mean relative attribute importance weights (NMD and diabetes studies), attribute uptake probability (MI study), or maximum acceptable risk (RA study).ResultsIn all four studies, attribute ranking showed similar patterns between DCE and other methods for the most important attributes. The same attribute had highest importance in three out of four studies. Significant differences were found in ranges of normalized preference measures of each study between DCE and the other methods: 4.1–43.4 versus 8.9–24.7 for DCE and BWS case 2 in NMD; 3.8–49.7 versus 11.9–16.8 for DCE and SW in diabetes; 2.0–85.5 versus 0.2–69.0 for DCE and BWS case 1 in MI; -3.5–49.2 versus 1.1–18.1 for DCE and PTT in RA.ConclusionsPreferences differed significantly between DCE and other preference methods implying limited convergent validity. The substantially larger ranges in normalized outcome measures in DCE compared to other methods, are likely due to differences in mechanics and bias related to the methods. Since none of the methods is considered the golden standard for measuring stated preferences as true preferences are unknown, further studies are necessary to compare stated preference methods, determine internal validity and data quality, and potentially measure external validity.

Purpose To quantify rheumatology patient preferences and willingness to pay (WTP) for features differentiating enhanced from standard self-injection devices and to investigate differences among subgroups. Patients and methods Patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA), and axial spondyloarthritis (axSpA) were recruited in the UK. A discrete-choice experiment was used to elicit preferences; respondents were presented with 10 choices between 3 different devices: a free standard disposable device, and 2 hypothetical reusable devices characterized by presence/absence of skin sensor, injection speed control, on-screen instructions, injection reminders, electronic log, and large grip. Every hypothetical device included a cost component to assess WTP for each enhanced feature. A random-parameters logit model was used to estimate preference weights and WTP. Results Data were collected from 323 respondents by electronic survey (15/11/2017-15/02/2018; RA: 108; PsA: 103; axSpA: 112). On average, the skin sensor was the most preferred feature (£30), followed by injection speed control, injection reminders, electronic log (~£20 each), on-screen instructions (~£12), and a device with a small, rather than large grip (~£7). Similar preferences for attributes were observed across condition subgroups except for grip size: axSpA patients preferred small grip (~£27); PsA patients preferred large grip (~£19). Overall, respondents preferred reusable devices with all enhanced features (WTP value: £85) over the standard device. RA patients exhibited a higher WTP (£145) than PsA (£102) or axSpA (£62) for the same enhanced device. Conclusion Patients positively valued reusable self-injection devices with enhanced features, which may improve patient experience, potentially improving treatment adherence, clinical, and economic outcomes.

Purpose: This study aimed to elicit patient and physician preferences for ulcerative colitis (UC) treatments in the United States (US). Patients and methods: The following UC treatment attributes included in the discrete-choice experiment (DCE) were identified during qualitative interviews with both patients and physicians: time to symptom improvement, chance of long-term symptom control, risks of serious infection and malignancy, mode and frequency of administration, and need for steroids. The DCE survey instruments were developed and administered to patients and physicians. A random-parameters logit model was used to estimate preference weights and conditional relative importance for these attributes. Results: A total of 200 patients with moderate to severe UC (status determined using self-reported medication history) and 200 gastroenterologists completed the survey. Patients' average age was 42 years; most (59%) were female. Patients considered symptom control 2.5 times as important as time to symptom improvement and 5-year risk of malignancy almost as important as long-term symptom control (relative importance, 0.79 vs 0.96 for long-term symptom control); they preferred oral to subcutaneous or intravenous administration (relative importance, 0.47 vs 0.11 and 0.18, respectively). For physicians, symptom control was the most important attribute and was five times as important as the risk of malignancy. Conclusion: Both patients and physicians considered long-term symptom control the most important attribute relative to others; however, risk of malignancy was of almost-equal importance to patients but not physicians. Differences between patients' and physicians' preferences highlight the need for improved communication about the relevant benefits and risks of different UC treatments to improve therapeutic decision-making.

Objectives Low optimism and low numeracy are associated with difficulty or lack of participation in making treatment-related health care decisions. We investigated whether low optimism and low self-reported numeracy scores could help uncover evidence of decisional conflict in a discrete-choice experiment (DCE). Methods Preferences for a treatment to delay type 1 diabetes were elicited using a DCE among 1501 parents in the United States. Respondents chose between two hypothetical treatments or they could choose no treatment (opt out) in a series of choice questions. The survey included a measure of optimism and a measure of subjective numeracy. We used latent class analyses where membership probability was predicted by optimism and numeracy scores. Results Respondents with lower optimism scores had a higher probability of membership in a class with disordered preferences ( P value for optimism coefficient = 0.032). Those with lower self-reported numeracy scores were more likely to be in a class with a strong preference for opting out and disordered preferences ( P = 0.000) or a class with a preference for opting out and avoiding serious treatment-related risks ( P = 0.015). Conclusions If respondents with lower optimism and numeracy scores are more likely to choose to opt out or have disordered preferences in a DCE, it may indicate that they have difficulty completing choice tasks.

Introduction. A growing literature has developed on identifying outcomes that matter to patients. This study demonstrates an approach involving patient and regulatory perspectives to identify outcomes that are meaningful in the context of medical devices for Parkinson’s disease (PD). Methods. A systematic process was used for specifying relevant regulatory endpoints by synthesizing inputs of various sources and stakeholders. First, a literature review was conducted to identify important benefits, risks, and other considerations for medical devices to treat PD; patient discussion groups ( n = 6) were conducted to refine the list of considerations, followed by a survey ( n = 29) to prioritize them; and patient and Food and Drug Administration (FDA) reviewers informed specification of the final endpoints. Two FDA clinicians gave clinical and regulatory perspectives at each step. Results. Movement symptoms were ranked as most important (ranked 1 or 2 by 72% of participants) and psychological and cognitive symptoms as the next most important (ranked 1 or 2 by 52% of participants). Within movement symptoms, falls, impaired movement, bradykinesia, resting tremor, stiffness, and rigidity were ranked highly. Overall, nine attributes were identified and prioritized as patient-centric for use in clinical trial design and quantitative patient preference studies. These attributes were benefits and risks related to therapeutics for PD as well as other considerations, including time until a medical device is available for patient use. Discussion. This prospective approach identified meaningful and relevant benefits, risks, and other considerations that may be used for clinical trial design and quantitative patient preference studies. Although PD was the focus of this study, the approach can be used to study patient perspectives about other disease or treatment areas.

Introduction: Gene therapies are innovative therapies that are increasingly being developed. However, health technology assessment (HTA) and payer decision making on these therapies is impeded by uncertainties, especially regarding long-term outcomes. Through measuring patient preferences regarding gene therapies, the importance of unique elements that go beyond health gain can be quantified and inform value assessments. We designed a study, namely the Patient preferences to Assess Value IN Gene therapies (PAVING) study, that can inform HTA and payers by investigating trade-offs that adult Belgian hemophilia A and B patients are willing to make when asked to choose between a standard of care and gene therapy. Methods and Analysis: An eight-step approach was taken to establish the protocol for this study: (1) stated preference method selection, (2) initial attributes identification, (3) stakeholder (HTA and payer) needs identification, (4) patient relevant attributes and information needs identification, (5) level identification and choice task construction, (6) educational tool design, (7) survey integration, and (8) piloting and pretesting. In the end, a threshold technique survey was designed using the attributes “Annual bleeding rate,” “Chance to stop prophylaxis,” “Time that side effects have been studied,” and “Quality of Life.” Ethics and Dissemination: The Medical Ethics Committee of UZ KU Leuven/Research approved the study. Results from the study will be presented to stakeholders and patients at conferences and in peer-reviewed journals. We hope that results from the PAVING study can inform decision makers on the acceptability of uncertainties and the value of gene therapies to patients., SCOPUS: ar.j, info:eu-repo/semantics/published

Objectives This study aimed to elicit preferences for psoriasis treatment features and to test for preference heterogeneity across groups of respondents. Materials and methods A discrete-choice experiment was employed to elicit preferences of patients with plaque psoriasis in multiple countries. The survey instrument included a series of choice questions between three hypothetical treatments, each characterized by varying levels of six attributes (namely, lesion reduction, risk of impairing side effects, time to reach results, mode and frequency of administration, itching reduction, and side effects). Random parameters logit was used to model the data. Results were compared across a total of 18 subgroup sets. Results The data analysis from 1,123 respondents showed that, on average, respondents receive more utility gain from higher levels of lesion reduction and lower risks of impairing side effects than changes in other attributes included in the study. Systematic differences were detected for 13 sets; the most pronounced differences were observed based on disease severity, nail psoriasis, biologic experience, and quality-of-life scores. Conclusion These many sources of preference heterogeneity identified by our analysis suggest that to improve patient satisfaction and, probably, adherence and persistence, clinicians should discuss options with patients when prescribing their treatment.

Background. Parkinson’s disease (PD) is neurodegenerative, causing motor, cognitive, psychological, somatic, and autonomic symptoms. Understanding PD patients’ preferences for novel neurostimulation devices may help ensure that devices are delivered in a timely manner with the appropriate level of evidence. Our objective was to elicit preferences and willingness-to-wait for novel neurostimulation devices among PD patients to inform a model of optimal trial design. Methods. We developed and administered a survey to PD patients to quantify the maximum levels of risks that patients would accept to achieve potential benefits of a neurostimulation device. Threshold technique was used to quantify patients’ risk thresholds for new or worsening depression or anxiety, brain bleed, or death in exchange for improvements in “on-time,” motor symptoms, pain, cognition, and pill burden. The survey elicited patients’ willingness to wait to receive treatment benefit. Patients were recruited through Fox Insight, an online PD observational study. Results. A total of 2740 patients were included and a majority were White (94.6%) and had a 4-year college degree (69.8%). Risk thresholds increased as benefits increased. Threshold for depression or anxiety was substantially higher than threshold for brain bleed or death. Patient age, ambulation, and prior neurostimulation experience influenced risk tolerance. Patients were willing to wait an average of 4 to 13 years for devices that provide different levels of benefit. Conclusions. PD patients are willing to accept substantial risks to improve symptoms. Preferences are heterogeneous and depend on treatment benefit and patient characteristics. The results of this study may be useful in informing review of device applications and other regulatory decisions and will be input into a model of optimal trial design for neurostimulation devices.

IntroductionAmidst growing consensus that stakeholder decision-making during drug development should be informed by an understanding of patient preferences, the Innovative Medicines Initiative project ‘Patient Preferences in Benefit-Risk Assessments during the Drug Life Cycle’ (PREFER) is developing evidence-based recommendations about how and when patient preferences should be integrated into the drug life cycle. This protocol describes a PREFER clinical case study which compares two preference elicitation methodologies across several populations and provides information about benefit–risk trade-offs by those at risk of rheumatoid arthritis (RA) for preventive interventions.Methods and analysisThis mixed methods study will be conducted in three countries (UK, Germany, Romania) to assess preferences of (1) first-degree relatives (FDRs) of patients with RA and (2) members of the public. Focus groups using nominal group techniques (UK) and ranking surveys (Germany and Romania) will identify and rank key treatment attributes. Focus group transcripts will be analysed thematically using the framework method and average rank orders calculated. These results will inform the treatment attributes to be assessed in a survey including a discrete choice experiment (DCE) and a probabilistic threshold technique (PTT). The survey will also include measures of sociodemographic variables, health literacy, numeracy, illness perceptions and beliefs about medicines. The survey will be administered to (1) 400 FDRs of patients with RA (UK); (2) 100 FDRs of patients with RA (Germany); and (3) 1000 members of the public in each of UK, Germany and Romania. Logit-based approaches will be used to analyse the DCE and imputation and interval regression for the PTT.Ethics and disseminationThis study has been approved by the London-Hampstead Research Ethics Committee (19/LO/0407) and the Ethics Committee of the Friedrich-Alexander-Universität Erlangen-Nürnberg (92_17 B). The protocol has been approved by the PREFER expert review board. The results will be disseminated widely and will inform the PREFER recommendations.

INTRODUCTION: Exploring patient perceptions regarding gene therapies may provide insights about their acceptability to patients. OBJECTIVE: To investigate opinions of people with haemophilia (PWH) regarding gene therapies. Moreover, this study aimed to identify patient-relevant attributes (treatment features) that influence PWH's treatment choices. METHODS: Semi-structured individual interviews were conducted with Belgian PWH, types A and B. A predefined interview guide included information sections and open, attribute ranking and case questions. Qualitative data were organized using NVivo 12 and analysed following framework analysis. Sum totals of scores obtained in the ranking exercise were calculated per attribute. RESULTS: In total, 20 PWH participated in the interviews. Most participants demonstrated a positive attitude towards gene therapy and were very willing (40%; n = 8) or willing (35%; n = 7) to receive this treatment. The following five attributes were identified as most important to PWH in making their choice: annual bleeding rate, factor level, uncertainty of long-term risks, impact on daily life, and probability that prophylaxis can be stopped. While participants were concerned about the uncertainty regarding long-term safety, most participants were less concerned about uncertainty regarding long-term efficacy. CONCLUSIONS: This qualitative study showed that most PWH have a positive attitude towards gene therapy and that besides efficacy, safety and the related uncertainties, also impact on daily life is important to patients. The identified patient-relevant attributes may be used by regulators, health technology assessment bodies and payers in their evaluation of gene therapies for haemophilia. Moreover, they may inform clinical trial design, pay-for-performance schemes and real-world evidence studies. ispartof: HAEMOPHILIA vol:27 issue:1 pages:129-136 ispartof: location:England status: published