Two Methods, One Story? Comparing Results of a Choice Experiment and Multidimensional Thresholding From a Clinician Preference Study in Aneurysmal Subarachnoid Hemorrhage.

OBJECTIVES: An increasing number of methods are used to elicit health preference information. It is unclear whether different elicitation methods produce similar results and policy advice. Here, we compared the results from a discrete choice experiment (DCE) and multidimensional thresholding (MDT) that were conducted in the same sample. METHODS: Clinicians (N = 350) completed a DCE and MDT to elicit their preferences for 4 attributes related to the medical management of subarachnoid hemorrhage after aneurysm repair. Preference weights were compared between the DCE and MDT using a complete combinatorial convolution test. Additionally, data from the DCE and MDT were used to compute preference-based net treatment values for 16 hypothetical treatment profiles versus 1000 simulated comparators. The implied treatment recommendations were compared between the DCE and MDT. RESULTS: Preference weight distributions and median weights did not differ significantly between the DCE and MDT for any attribute: likelihood of delayed cerebral ischemia (medians 0.48 vs 0.40; P = .41), risk of lung complications (medians 0.27 vs 0.30; P = .52), risk of hypotension (medians 0.10 vs 0.11; P = .55), and risk of anemia (medians 0.07 vs 0.07; P = .50). The DCE and MDT produced similar treatment net value distributions (P > .05) and implied the same treatment recommendations in 82.3% of cases. CONCLUSIONS: The DCE and MDT elicited similar preference distributions and produced the same treatment recommendations for most tested cases. However, the share of people supporting the average treatment recommendation differed. More research is needed to determine how these findings would compare with those in other populations (in particular, patients) and applications.

Preferences for innovations in healthcare delivery models in the Swiss elderly population: a latent class, choice modelling study.

BACKGROUND: With the increasing number of people affected by multiple chronic conditions, it is essential for public-health professionals to promote strategies addressing patient needs for coordinated care. We aim to explore preference heterogeneity for better-coordinated care delivery models in Swiss older adults, and identify profiles of individuals more open to healthcare reforms. METHODS: A DCE (discrete choice experiment) survey was developed online and on paper for the Swiss adults aged 50+, following best practice. To elicit preferences, we estimated a latent class model allowing grouping individuals with similar preferences into distinct classes, and examined what background characteristics contributed to specific class membership. RESULTS: The optimal model identified three classes with different openness to reforms. Class 1 (49%) members were concerned with premium increases and were in favour of integrated care structures with care managed by interprofessional teams. Individuals in class 2 (19%) were younger, open to reforms, and expressed the needs for radical changes within the Swiss healthcare system. Class 3 respondents (32%) were strongly reluctant to changes. CONCLUSIONS: Our study goes beyond average preferences and identifies three distinct population profiles, a majority open to reforms on specific aspects of care delivery, a smallest group in favour radical changes, and a third strongly against changes. Therefore, tailored approaches around healthcare reforms are needed, e.g. explaining the role of interprofessional teams in coordinating care, electronic health records and insurance premium variation.

Current Health State Affected Patient Preferences More Than Disease Status: A Discrete Choice Experiment in Multiple Myeloma.

OBJECTIVES: To examine how disease status and current health state influence treatment preferences of patients with multiple myeloma (MM). METHODS: Participants with MM from France, Germany, and the United Kingdom completed a web-based survey that included a discrete choice experiment (DCE) and EQ-5D assessment. The DCE elicited preferences for 8 attributes: increased life expectancy, increased time to relapse, pain, fatigue, risk of infection, administration (route and duration), frequency of administration, and monitoring. Multinomial logit models were used to analyze DCE preference data and to calculate life expectancy trade-offs. RESULTS: Three hundred participants with MM (newly diagnosed, transplant eligible, n = 108; newly diagnosed, transplant ineligible, n = 105; relapsed-refractory, n = 87) completed the survey. The most valued attributes were pain, fatigue, and increased life expectancy. Participants would want an additional 2.7 years of life expectancy (95% confidence interval [CI] 2.4-3.1 years) to tolerate extreme pain and an additional 2.0 years of life expectancy (95% CI 1.6-2.3 years) to tolerate constant fatigue. Participants in a better health state (third EQ-5D score quartile [0.897]) required less additional life expectancy than participants with a worse health state (first EQ-5D score quartile [0.662]) to tolerate extreme pain (2.3 years [95% CI 1.9-2.6 years] vs 3.0 years [95% CI 2.6-3.4 years]; P = .007). There was little difference in treatment preferences between newly diagnosed and relapsed-refractory patients for pain, fatigue, and increased life expectancy. CONCLUSIONS: Current health state influenced treatment preferences of patients with MM more than disease status and should be considered when making treatment decisions.

Keeping an eye on cost: What can eye tracking tell us about attention to cost information in discrete choice experiments?

Concern has been expressed about including a cost attribute within discrete choice experiments (DCEs) when individuals do not have to pay at the point of consumption. We use eye tracking to investigate attention to cost when valuing publicly financed health care. One-hundred and four individuals completed a DCE concerned with preferences for UK general practitioner appointments: 51 responded to a DCE with cost included and 53 to the same DCE without cost. Eye-movements were tracked whilst respondents completed the DCE. We assessed if respondents pay attention to cost. We then compare fixation time (FT) on attributes, eye movement patterns and mental effort across the experimental groups. Results are encouraging for the inclusion of cost in DCEs valuing publicly provided healthcare. Most respondents gave visual attention to the cost attribute most of the time. Average FT on multi-attribute tasks increased by 44% in the cost DCE, with attention to non-monetary attributes increasing by 22%. Including cost led to more structured decision-making and did not increase mental effort. Acceptability of the cost attribute and difficulty of choice tasks were predictors of cost information processing, highlighting the importance of both motivating the cost attribute and considering difficulty of the tasks when developing DCEs.

How do study design features and participant characteristics influence willingness to participate in clinical trials? Results from a choice experiment.

BACKGROUND: Research about the decision to participate in a clinical study has tended to be limited to single indications and has focused on narrow sets of study and participant characteristics. This study applied stated preference methods to understand the clinical trial design attributes that most influence willingness to participate and how this varied with participant characteristics. METHODS: Adults residing in the US, China, or Poland with a self-reported diagnosis of cancer, heart disease, migraine, rheumatoid arthritis, or multiple sclerosis completed an online survey. Participants were asked whether they would participate in clinical studies defined by seventeen attributes within five categories (payment/support, administration/procedures, treatment-related, study location/time commitment, and data collection/feedback). Participants saw six different hypothetical clinical study profiles. Depending on their participation decision to an initial clinical study profile, the subsequent five questions had one design attribute (randomly selected per question) consecutively improved or deteriorated to elicit preferences. A logistic regression was used to determine which participant characteristics influenced participation decisions. A latent class logit model was used to identify how the influence of study design features varied between participants and whether groups of participants with similar preferences could be identified. RESULTS: The survey was completed by 487 participants (32% China, 35% Poland, 33% US; 8%-19% per indication). Willingness to participate was found to be a function of participant age, certain elements of quality of life, and previous treatment experience, in particular number of lines of treatment received and experience of adverse events. Willingness to participate was influenced by study design features such as payment, study duration, and time commitment - both the overall time and whether the time was at home or away from home, with the latter being particularly relevant to participants experiencing fatigue due to their disease. CONCLUSIONS: This study quantifies how study designs influence willingness to participate and how this varies with participant types. These findings suggest that it is how an indication influences quality of life and treatment experience, rather than the indication alone, that impacts participation rates, opening the way for insights that are transferrable across indications, which may be particularly useful when considering rare diseases.

Patient preferences for frontline therapies for Philadelphia chromosome-positive acute lymphoblastic leukemia: a discrete choice experiment.

Aim: We examined the preferences of adults with Philadelphia chromosome-positive acute lymphoblastic leukemia (Ph+ ALL) for benefits and risks of tyrosine kinase inhibitors combined with chemotherapy for first-line treatment. Methods: In a discrete choice experiment, 201 patients chose between hypothetical treatment alternatives with varied levels of remission duration and overall survival (OS), and risks of major cardiovascular (CV) events and myelosuppression. Results: Although OS was the most important attribute to patients with Ph+ ALL, they were willing to tolerate a 2.9% increase in CV risk for 1 additional month of OS. Older patients (>59 years) and patients not in remission were less likely to tolerate increased CV risk. Conclusion: Preferences and risk tolerance varied between patients, highlighting the importance of shared decision making when selecting treatments for Ph+ ALL.

Treatments differ in their potential benefits and side effects they may come with. Patients should be involved in deciding which treatments they receive. This is because patients may have different views than physicians on how the benefits and side effects of treatment would affect their quality of life. Additionally, patients may have different risk tolerances. This study shows how patients with a form of leukemia valued survival benefits and side effects of treatments, and the trade-offs that they were willing to make between these. On average, longer survival had most value to patients. They were willing to accept a higher risk of a major cardiovascular side effect (e.g., having a stroke) if the treatment would allow them to live longer. However, not all patients had the same opinion, and some groups of patients were less willing to accept risks to receive longer survival. By involving patients in treatment decisions, we can help ensure they receive treatments that match their personal preferences.

Weighting or aggregating? Investigating information processing in multi-attribute choices.

Multi-attribute choices are commonly analyzed in economics to value goods and services. Analysis assumes individuals consider all attributes, making trade-offs between them. Such decision-making is cognitively demanding, often triggering alternative decision rules. We develop a new model where individuals aggregate multi-attribute information into meta-attributes. Applying our model to a choice experiment (CE) dataset, accounting for attribute aggregation (AA) improves model fit. The probability of adopting AA is greater for: homogenous attribute information; participants who had shorter response time and failed the dominance test; and for later located choices. Accounting for AA has implications for welfare estimates. Our results underline the importance of accounting for information processing rules when modelling multi-attribute choices.

Evaluating the Trade-Offs Men with Localized Prostate Cancer Make between the Risks and Benefits of Treatments: The COMPARE Study.

PURPOSE: The COMPARE (COMparing treatment options for ProstAte cancer) study aimed to evaluate and quantify the trade-offs patients make between different aspects of active surveillance and definitive therapy. MATERIALS AND METHODS: A discrete choice experiment tool was used to elicit patient preferences for different treatment characteristics in 34 urology departments. Patients with localized prostate cancer completed the discrete choice experiment within 1 week of being diagnosed and before they made treatment decisions. The discrete choice experiment was pretested (5) and piloted (106) with patients. Patients chose their preferred treatment profile based on the 6 characteristics of treatment type (active surveillance, focal therapy, radical therapy), return to normal activities, erectile function, urinary function, not needing more cancer treatment and 10 to 15-year cancer specific survival. Different tools were designed for patients with low-intermediate (468) and high risk (166) disease. An error components conditional logit model was used to estimate preferences and trade-offs between treatment characteristics. RESULTS: Patients with low-intermediate risk disease were willing to trade 6.99% absolute decrease in survival to have active surveillance over definitive therapy. They were willing to trade 0.75%, 0.46% and 0.19% absolute decrease in survival for a 1-month reduction in time to return to normal activities and 1% absolute improvements in urinary and sexual function, respectively. Patients with high risk disease were willing to trade 3.10%, 1.04% and 0.41% absolute decrease in survival for a 1-month reduction in time to return to normal activities and 1% absolute improvements in urinary and sexual function, respectively. CONCLUSIONS: Patients with low-intermediate risk prostate cancer preferred active surveillance to definitive therapy. Patients of all risk levels were willing to trade cancer specific survival for improved quality of life.

U.K. Intensivists' Preferences for Patient Admission to ICU: Evidence From a Choice Experiment.

OBJECTIVES: Deciding whether to admit a patient to the ICU requires considering several clinical and nonclinical factors. Studies have investigated factors associated with the decision but have not explored the relative importance of different factors, nor the interaction between factors on decision-making. We examined how ICU consultants prioritize specific factors when deciding whether to admit a patient to ICU. DESIGN: Informed by a literature review and data from observation and interviews with ICU clinicians, we designed a choice experiment. Senior intensive care doctors (consultants) were presented with pairs of patient profiles and asked to prioritize one of the patients in each task for admission to ICU. A multinomial logit and a latent class logit model was used for the data analyses. SETTING: Online survey across U.K. intensive care. SUBJECTS: Intensive care consultants working in NHS hospitals. MEASUREMENTS AND MAIN RESULTS: Of the factors investigated, patient's age had the largest impact at admission followed by the views of their family, and severity of their main comorbidity. Physiologic measures indicating severity of illness had less impact than the gestalt assessment by the ICU registrar. We identified four distinct decision-making patterns, defined by the relative importance given to different factors. CONCLUSIONS: ICU consultants vary in the importance they give to different factors in deciding who to prioritize for ICU admission. Transparency regarding which factors have been considered in the decision-making process could reduce variability and potential inequity for patients.

For better or worse? Investigating the validity of best-worst discrete choice experiments in health.

Discrete choice experiments (DCEs) are frequently used in health economics to measure preferences for nonmarket goods. Best-worst discrete choice experiment (BWDCE) has been proposed as a variant of the traditional "pick the best" approach. BWDCE, where participants choose the best and worst options, is argued to generate more precise preference estimates because of the additional information collected. However, the validity of the approach relies on two necessary conditions: (a) best and worst decisions provide similar information about preferences and (b) asking individuals to answer more than one choice question per task does not reduce data quality. Whether these conditions hold in empirical applications remains under researched. This is the first study to compare participants' choices across three experimental conditions: (a) BEST choices only, (b) WORST choices only, and (c) BEST and WORST choices (BWDCE). We find responses to worst choices are noisier. Implied preferences from the best only and worst only choices are qualitatively different, leading to different WTP values. Responses to BWDCE tasks have lower consistency, and respondents are more likely to use simplifying decision heuristics. We urge caution in using BWDCE as an alternative to the traditional "pick the best" DCE.

For more than money: willingness of health professionals to stay in remote Senegal.

BACKGROUND: Poor distribution of already inadequate numbers of health professionals seriously constrains equitable access to health services in low- and middle-income countries. The Senegalese Government is currently developing policy to encourage health professionals to remain in areas defined as 'difficult'. Understanding health professional's preferences is crucial for this policy development. METHODS: Working with the Senegalese Government, a choice experiment (CE) was developed to elicit the job preferences of physicians and non-physicians. Attributes were defined using a novel mixed-methods approach, combining interviews and best-worst scaling (Case 1). Six attributes were categorised as 'individual (extrinsic) incentive' attributes ('type of contract', 'provision of training opportunities', 'provision of an allowance' and 'provision of accommodation') or 'functioning health system' attributes ('availability of basic equipment in health facilities' and 'provision of supportive supervision by health administrators'). Using face-to-face interviews, the CE was administered to 55 physicians (3909 observations) and 246 non-physicians (17 961 observations) randomly selected from those working in eight 'difficult' regions in Senegal. Conditional logit was used to analyse responses. This is the first CE to both explore the impact of contract type on rural retention and to estimate value of attributes in terms of willingness to stay (WTS) in current rural post. RESULTS: For both physicians and non-physicians, a permanent contract is the most important determinant of rural job retention, followed by availability of equipment and provision of training opportunities. Retention probabilities suggest that policy reform affecting only a single attribute is unlikely to encourage health professionals to remain in 'difficult' regions. The relative importance of an allowance is low; however, the level of such financial incentives requires further investigation. CONCLUSION: Contract type is a key factor impacting on retention. This has led the Senegalese Health Ministry to introduce a new rural assignment policy that recruits permanent staff from the pool of annually contracted healthcare professionals on the condition that they take up rural posts. While this is a useful policy development, further efforts to retain rural health workers, considering both personal incentives and the functioning of health systems, are necessary to ensure health worker numbers are adequate to meet the needs of rural communities.

The eyes have it: Using eye tracking to inform information processing strategies in multi-attributes choices.

Although choice experiments (CEs) are widely applied in economics to study choice behaviour, understanding of how individuals process attribute information remains limited. We show how eye-tracking methods can provide insight into how decisions are made. Participants completed a CE, while their eye movements were recorded. Results show that although the information presented guided participants' decisions, there were also several processing biases at work. Evidence was found of (a) top-to-bottom, (b) left-to-right, and (c) first-to-last order biases. Experimental factors-whether attributes are defined as "best" or "worst," choice task complexity, and attribute ordering-also influence information processing. How individuals visually process attribute information was shown to be related to their choices. Implications for the design and analysis of CEs and future research are discussed.

Is Best-Worst Scaling Suitable for Health State Valuation? A Comparison with Discrete Choice Experiments.

Health utility indices (HUIs) are widely used in economic evaluation. The best-worst scaling (BWS) method is being used to value dimensions of HUIs. However, little is known about the properties of this method. This paper investigates the validity of the BWS method to develop HUI, comparing it to another ordinal valuation method, the discrete choice experiment (DCE). Using a parametric approach, we find a low level of concordance between the two methods, with evidence of preference reversals. BWS responses are subject to decision biases, with significant effects on individuals' preferences. Non parametric tests indicate that BWS data has lower stability, monotonicity and continuity compared to DCE data, suggesting that the BWS provides lower quality data. As a consequence, for both theoretical and technical reasons, practitioners should be cautious both about using the BWS method to measure health-related preferences, and using HUI based on BWS data. Given existing evidence, it seems that the DCE method is a better method, at least because its limitations (and measurement properties) have been extensively researched. Copyright © 2016 John Wiley & Sons, Ltd.

What do UK medical students value most in their careers? A discrete choice experiment.

CONTEXT: Many individual- and job-related factors are known to influence medical careers decision making. Previous research has extensively studied medical trainees' (residents') and students' views of the factors that are important. However, how trainees and students trade off these factors at times of important careers-related decision making is under-researched. Information about trade-offs is crucial to the development of effective policies to enhance the recruitment and retention of junior doctors. OBJECTIVES: Our aim was to investigate the strength of UK medical students' preferences for the characteristics of training posts in terms of monetary value. METHODS: We distributed a paper questionnaire that included a discrete choice experiment (DCE) to final-year medical students in six diverse medical schools across the UK. The main outcome measure was the monetary value of training post characteristics, based on willingness to forgo and willingness to accept extra income for a change in each job characteristic calculated from regression coefficients. RESULTS: A total of 810 medical students answered the questionnaire. The presence of good working conditions was by far the most influential characteristic of a training position. Medical students consider that, as newly graduated doctors, they will require compensation of an additional 43.68% above average earnings to move from a post with excellent working conditions to one with poor working conditions. Female students value excellent working conditions more highly than male students, whereas older medical students value them less highly than younger students. CONCLUSIONS: Students on the point of completing medical school and starting postgraduate training value good working conditions significantly more than they value desirable geographical location, unit reputation, familiarity with the unit or opportunities for partners or spouses. This intelligence can be used to address the crisis in workforce staffing that has developed in the UK and opens up fruitful areas for future research across contexts and in terms of examining stated preferences versus actual career-related behaviour.

What do UK doctors in training value in a post? A discrete choice experiment.

CONTEXT: Many individual and job-related factors are known to influence medical careers decision making. Medical trainees' (residents) views of which characteristics of a training post are important to them have been extensively studied but how they trade-off these characteristics is under-researched. Such information is crucial for the development of effective policies to enhance recruitment and retention. Our aim was to investigate the strength of UK foundation doctors' and trainees' preferences for training post characteristics in terms of monetary value. METHODS: We used an online questionnaire study incorporating a discrete choice experiment (DCE), distributed to foundation programme doctors and doctors in training across all specialty groups within three UK regions, in August-October 2013. The main outcome measures were monetary values for training-post characteristics, based on willingness to forgo and willingness to accept extra income for a change in each job characteristic, calculated from regression coefficients. RESULTS: The questionnaire was answered by 1323 trainees. Good working conditions were the most influential characteristics of a training position. Trainee doctors would need to be compensated by an additional 49.8% above the average earnings within their specialty to move from a post with good working conditions to one with poor working conditions. A training post with limited rather than good opportunities for one's spouse or partner would require compensation of 38.4% above the average earnings within their specialty. Trainees would require compensation of 30.8% above the average earnings within their specialty to move from a desirable to a less desirable locality. These preferences varied only to a limited extent according to individual characteristics. DISCUSSION: Trainees place most value on good working conditions, good opportunities for their partners and desirable geographical location when making career-related decisions. This intelligence can be used to develop alternative models of workforce planning or to develop information about job opportunities that address trainees' values.

Empirical Testing of the External Validity of a Discrete Choice Experiment to Determine Preferred Treatment Option: The Case of Sleep Apnea.

There is an increasing use of the discrete choice experiment (DCE) method in health care to estimate preferences of individuals and the public for different services. Despite this increasing use, there are few studies that investigate the validity of the DCE in health. This study investigates the external validity of DCE by comparing the predicted treatment choices from the DCE to the actual treatment choices made by the same respondents using a decision board (DB) approach. The sample includes 140 patients who came for a sleep apnea routine visit in a hospital setting. Each respondent answered 10 DCE tasks and 1 DB task. The preferences were estimated with a generalized multinomial logit model and the predicted and actual treatment choices were compared both at the sample and individual levels. The results raise questions about the external validity of DCE in health. At the sample level, the comparison showed large but not significant differences between the two methods. This can be explained in part by the aggregation process that obscures variability in the individuals' preferences. At the individual level, the comparison showed that the two methods led to significantly different patterns of choices.

What are the patients' preferences for the Chronic Care Model? An application to the obstructive sleep apnoea syndrome.

CONTEXT: The Chronic Care Model (CCM) has been developed to improve the quality of medical care delivered by general practitioners to patients with multiple chronic conditions. Despite an increasing use of this model, it remains unclear to what extent the different recommendations are valued by the patients. OBJECTIVE: This study aims to identify the preferences of patients with multiple chronic conditions for recommendations of the Chronic Care Model. METHODS: The patients' preferences were identified with a discrete choice experiment. The hypothetical general practice cares were described using 10 recommendations of the Chronic Care Model (i.e. shared decision making; informational continuity (INF); regular follow-up; planned care; communication; collaboration with a nurse; advices on health habits; patient empowerment; psychological support; coordination). Respondents were consecutively recruited in a hospital setting during routine follow-up visits to their pulmonary specialist. The sample of respondents included 150 patients with multiple chronic conditions in addition to an obstructive sleep apnoea syndrome. RESULTS: The INF is highly valued by the patients. At the opposite, patients do not appear to value collaboration between nurses and GPs. To a large extent, the patients' preferences for the recommendations of the CCM depend on their gender, number of chronic conditions and self-perceived health condition. DISCUSSION: The INF appeared to be a minimal requirement to ensure high-quality general practice care. The significant interactions between the patients' socio-demographic characteristics and their preferences for the CCM highlighted the necessity to deliver personalized services.

Adaptation and validation of the patient assessment of chronic illness care in the French context.

BACKGROUND: Chronic diseases are major causes of disability worldwide with rising prevalence. Most patients suffering from chronic conditions do not always receive optimal care. The Chronic Care Model (CCM) has been developed to help general practitioners making quality improvements. The Patient Assessment of Chronic Illness Care (PACIC) questionnaire was increasingly used in several countries to appraise the implementation of the CCM from the patients' perspective. The objective of this study was to adapt the PACIC questionnaire in the French context and to test the validity of this adaptation in a sample of patients with multiple chronic conditions. METHODS: The PACIC was translated into French language using a forward/backward procedure. The French version was validated using a sample of 150 patients treated for obstructive sleep apnea syndrome (OSAS) and having multiple chronic co-morbidities. Several forms of validity were analysed: content; face; construct; and internal consistency. The construct validity was investigated with an exploratory factorial analysis. RESULTS: The French-version of the PACIC consisted in 18 items, after merging two pairs of items due to redundancy. The high number of items exhibiting floor/ceiling effects and the non-normality of the ratings suggested that a 5-points rating scale was somewhat inappropriate to assess the patients' experience of care. The construct validity of the French-PACIC was verified and resulted in a bi-dimensional structure. Overall this structure showed a high level of internal consistency. The PACIC score appeared to be significantly related to the age and self-reported health of the patients. CONCLUSIONS: A French-version of the PACIC questionnaire is now available to evaluate the patients' experience of care and to monitor the quality improvements realised by the medical structures. This study also pointed out some methodological issues about the PACIC questionnaire, related to the format of the rating scale and to the structure of the questionnaire.

Patients' Preferences for Systemic Lupus Erythematosus Treatments-A Discrete Choice Experiment.

BACKGROUND: Symptoms of systemic lupus erythematosus (SLE) vary between patients, but those of increased disease activity typically include musculoskeletal and mucocutaneous manifestations such as joint pain, swelling, and rashes. Several treatment options are available to patients with SLE with variable efficacy. Many treatments, especially corticosteroids, cause unwanted side effects, although little is currently known about patients' preferences for treatments of SLE. OBJECTIVE: We aimed to identify which attributes of SLE treatment are valued by patients and to quantify their relative importance. METHODS: Adult participants with moderate-to-severe SLE were asked to make a series of choices between two hypothetical treatments in an online discrete choice experiment (DCE). A latent class model (LCL) was estimated to analyze choice data. Relative attribute importance (RAI) was calculated to determine the importance of each attribute to participants. RESULTS: A total of 342 participants from the USA completed the survey. A three-class LCL model was found to have the best fit. Class 1 (non-attenders) had non-significant preferences across all attributes. To achieve a better fit, a constrained LCL (cLCL) model was run with the two remaining classes. The most important attributes for participants in class 2 (benefit-seekers) were joint pain (RAI = 32.0%), non-joint pain (RAI = 21.8%), fatigue (RAI = 20.1%), and skin rashes and itching (RAI = 19.1%). The most important attributes for participants in class 3 (risk-avoiders) were risk of non-severe side effects from corticosteroids (RAI = 28.4%), risk of severe side effects from corticosteroids (RAI = 21.4%), and the risk of infections (RAI = 19.2%). Risk-avoiders were more likely to have been diagnosed with SLE for a longer period (>1 year) and were more likely to have experience with oral corticosteroids. CONCLUSIONS: SLE patients fall into two groups with distinct preferences: benefit-seekers, who prioritize reducing the impact of disease symptoms, and risk-avoiders, who prioritize avoiding treatment risks. The implication of this finding will depend on the reasons for these differences, which warrant further research. Our study suggests that these differences arise due to the impact of disease and treatment experience on preferences. If so, well-informed patients may not be willing to tolerate the risks associated with oral corticosteroids in exchange for their benefits.

Treatment preferences of adults and adolescents with alopecia areata: A discrete choice experiment.

PRODUCTS with janus kinase (JAK) inhibition have been shown to promote hair regrowth in patients with alopecia areata (AA). To guide drug-approval and treatment decisions, it is important to understand patients' willingness to accept the potential risks of JAK inhibition in exchange for potential benefits. We quantified the treatment preferences of adult (≥18 years) and adolescent patients (12-17 years) with AA in the US and Europe to determine the trade-offs they are willing to make between benefits and risks. Preferences for oral AA treatment attributes were elicited using a discrete choice experiment consisting of 12 tasks in which patients chose between two hypothetical treatment alternatives and no treatment. Benefits included the probability of 80%-100% scalp hair regrowth (Severity of Alopecia Tool score ≤ 20) and achieving moderate-to-normal eyebrow and eyelash hair. Treatment-related risks included 3-year probabilities of serious infection, cancer, and blood clots. Preference estimates were used to calculate the maximum level of each risk that patients were willing to accept for increases in treatment benefits. The most important attribute to both adults (n = 201) and adolescents (n = 120) was a 50% probability of achieving hair regrowth on most or all the scalp; however, adolescents placed greater relative importance on this attribute than did adults. Adults were averse to the risks of serious infection, cancer, and blood clots, whereas adolescents were averse to the risk of cancer. For a 20% increase in the probability of 80%-100% scalp hair regrowth, adults were willing to accept a mean (95% confidence interval) 3-year risk of serious infection, cancer, and blood clots of 7.4% (5.5-9.3), 2.5% (1.9-3.1), and 9.3% (6.4-12.2). Adolescents were willing to accept a 3-year risk of cancer of 3.3% (2.4-4.2). Patients with AA in the US and Europe are willing to accept substantial risks to obtain an effective treatment.