Patient-Centered Identification of Meaningful Regulatory Endpoints for Medical Devices to Treat Parkinson's Disease.

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.

Quantitative Benefit-Risk Assessment: State of the Practice Within Industry.

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.

Physicians' preferences for bone metastases treatments in France, Germany and the United Kingdom.

BACKGROUND: Several bone-targeted agents (BTAs) are available for preventing skeletal-related events (SREs), but they vary in terms of efficacy, safety and mode of administration. This study assessed data on European physicians' treatment preferences for preventing SREs in patients with bone metastases from solid tumours. METHODS: Physicians completed a web-based discrete-choice experiment survey of 10 choices between pairs of profiles of hypothetical BTAs for a putative patient. Each profile included five attributes within a pre-defined range (primarily based on existing BTAs' prescribing information): time (months) until the first SRE; time (months) until worsening of pain; annual risk of osteonecrosis of the jaw (ONJ); annual risk of renal impairment; and mode of administration. Choice questions were developed using an experimental design with known statistical properties. A separate main-effects random parameters logit model was estimated for each country and provided the relative preference for the treatment attributes in the study. RESULTS: A total of 191 physicians in France, 192 physicians in Germany, and 197 physicians in the United Kingdom completed the survey. In France and the United Kingdom, time until the first SRE and risk of renal impairment were the most important attributes; in Germany, time until the first SRE and delay in worsening of pain were the most important. In all countries, a 120-min infusion every 4 weeks was the least preferred mode of administration (p < 0.05) and the annual risk of ONJ was judged to be the least important attribute. CONCLUSIONS: When making treatment decisions regarding the choice of BTA, delaying the onset of SREs/worsening of pain and reducing the risk of renal impairment are the primary objectives for physicians.

Conducting a Discrete-Choice Experiment Study Following Recommendations for Good Research Practices: An Application for Eliciting Patient Preferences for Diabetes Treatments.

OBJECTIVES: To consolidate and illustrate good research practices in health care to the application and reporting of a study measuring patient preferences for type 2 diabetes mellitus medications, given recent methodological advances in stated-preference methods. METHODS: The International Society for Pharmacoeconomics and Outcomes Research good research practices and other recommendations were used to conduct a discrete-choice experiment. Members of a US online panel with type 2 diabetes mellitus completed a Web-enabled, self-administered survey that elicited choices between treatment pairs with six attributes at three possible levels each. A D-efficient experimental design blocked 48 choice tasks into three 16-task surveys. Preference estimates were obtained using mixed logit estimation and were used to calculate choice probabilities. RESULTS: A total of 552 participants (51% males) completed the survey. Avoiding 90 minutes of nausea was valued the highest (mean -10.00; 95% confidence interval [CI] -10.53 to -9.47). Participants wanted to avoid low blood glucose during the day and/or night (mean -3.87; 95% CI -4.32 to -3.42) or one pill and one injection per day (mean -7.04; 95% CI -7.63 to -6.45). Participants preferred stable blood glucose 6 d/wk (mean 4.63; 95% CI 4.15 to 5.12) and a 1% decrease in glycated hemoglobin (mean 5.74; 95% CI 5.22 to 6.25). If cost increased by $1, the probability that a treatment profile would be chosen decreased by 1%. CONCLUSIONS: These results are consistent with the idea that people have strong preferences for immediate consequences of medication. Despite efforts to produce recommendations, ambiguity surrounding good practices remains and various judgments need to be made when conducting stated-preference studies. To ensure transparency, these judgments should be described and justified.

Improving the quality of discrete-choice experiments in health: how can we assess validity and reliability?

INTRODUCTION: The recent endorsement of discrete-choice experiments (DCEs) and other stated-preference methods by regulatory and health technology assessment (HTA) agencies has placed a greater focus on demonstrating the validity and reliability of preference results. Areas covered: We present a practical overview of tests of validity and reliability that have been applied in the health DCE literature and explore other study qualities of DCEs. From the published literature, we identify a variety of methods to assess the validity and reliability of DCEs. We conceptualize these methods to create a conceptual model with four domains: measurement validity, measurement reliability, choice validity, and choice reliability. Each domain consists of three categories that can be assessed using one to four procedures (for a total of 24 tests). We present how these tests have been applied in the literature and direct readers to applications of these tests in the health DCE literature. Based on a stakeholder engagement exercise, we consider the importance of study characteristics beyond traditional concepts of validity and reliability. Expert commentary: We discuss study design considerations to assess the validity and reliability of a DCE, consider limitations to the current application of tests, and discuss future work to consider the quality of DCEs in healthcare.

Preferences for Multiple Sclerosis Treatments: Using a Discrete-Choice Experiment to Examine Differences Across Subgroups of US Patients.

BACKGROUND: The growing number of treatments for relapsing multiple sclerosis (MS) provides opportunities to consider patient preferences in treatment decisions. METHODS: We designed a Web-based, discrete-choice experiment survey to analyze treatment preferences in patients with relapsing-remitting MS (RRMS). The survey presented hypothetical MS treatments defined by six attributes: risk of MS progression, time between relapses, risk of serious infection, treatment-related flu-like symptoms and gastrointestinal symptoms, and route and frequency of administration. Preference weights estimated with random-parameters logit were used to calculate importance scores and preference shares among three pairs of subsamples. RESULTS: Patients with a self-reported physician diagnosis of RRMS (N = 301) completed the survey: 56% rated their disability level as normal or mild; 43% currently used a self-injectable treatment. Respondents with normal or mild disability levels placed greater weight on avoiding injections with flu-like symptoms and risk of progression, whereas patients with worse disability placed greater weight on reducing risk of progression and risk of serious infection. Patients taking injectables placed the most weight on risk of progression and risk of serious infection, whereas respondents not taking injectables placed the most weight on route and frequency of administration. Differences in preferences between subgroups were significant (P < .05). The presence of common adverse events associated with daily pills and injectables altered predicted preferences for route of administration. CONCLUSIONS: Preferences of patients with RRMS varied depending on current treatment and disability level, especially regarding mode of administration. Considering patient preferences for treatment features may lead to higher treatment satisfaction and adherence.

Quantifying the relative importance to patients of avoiding symptoms and outcomes of heart failure.

OBJECTIVE: To evaluate heart failure (HF) patients' disease knowledge and preferences for avoiding different disease outcomes. METHODS: An online survey was administered to 400 individuals with a self-reported diagnosis of HF to elicit relative importance weights (RIWs) for avoiding 11 potential HF symptoms and outcomes using best-worst scaling. The survey also included questions about individuals' HF knowledge, and demographic and disease-experience characteristics. Differences in RIWs among sub-groups, defined by HF knowledge, caregiver support, age, recent hospitalization or emergency room visit for HF, health-related quality-of-life, and cardiac device experience were examined. RESULTS: Relative to limitations in usual activities (RIW 1.00), respondents preferred avoiding severe, infrequent cardiovascular events (e.g. stroke [RIW 8.51], heart transplant [RIW 7.84], or heart attack [RIW 5.3]) most, followed by difficulty breathing (RIW 2.55), inability to enjoy life (RIW 1.84), cardiac device implantation (RIW 1.74), and atrial fibrillation (RIW 1.57). Patients preferred avoiding swelling (RIW 0.47) and fatigue (RIW 0.58) least. RIWs for avoiding severe, infrequent events were higher among those with high disease knowledge, those without caregivers, and those without a recent hospitalization or emergency room visit. CONCLUSIONS: Patients' preferences for avoiding HF outcomes vary across outcomes and by individuals' knowledge, caregiver status, and age. Healthcare providers should solicit and incorporate insights about patients' knowledge of HF and their preferences for avoiding HF outcomes into HF education and management planning efforts.

Benefit-risk tradeoff preferences for chronic hand eczema treatments.

Hand eczema affects approximately 16% of the US population. The long-term prognosis is poor, and 5-7% experience severe chronic hand eczema (sCHE) that interferes with daily activities. Treatments for CHE may be ineffective or associated with adverse events (AEs) that may dissuade patients from pursuing or continuing treatment. For quantification of patient experiences and benefit-risk preferences for outcomes associated with CHE treatments, a web-based discrete choice experiment survey was administered to patients in the United States with a self-reported physician diagnosis of CHE and severe symptoms not resolved with topical agents. Respondents answered a series of treatment choice questions, each requiring evaluation of a pair of hypothetical profiles of medications for sCHE defined by efficacy and risk of several AEs. Improvement in CHE clearing of 25-50% was rated from 1.5 to 3.1 times as important as eliminating a 5% risk of permanent bone problems. The mean maximum acceptable risk of permanent vision problems in exchange for an improvement in CHE clearing of 25-50% ranged from 3.4% to 4.8%. This study demonstrated that patients with CHE rated efficacy improvements associated with treatment of sCHE as more important than eliminating the risks of specific AEs.

Weighing Clinical Evidence Using Patient Preferences: An Application of Probabilistic Multi-Criteria Decision Analysis.

The need for patient engagement has been recognized by regulatory agencies, but there is no consensus about how to operationalize this. One approach is the formal elicitation and use of patient preferences for weighing clinical outcomes. The aim of this study was to demonstrate how patient preferences can be used to weigh clinical outcomes when both preferences and clinical outcomes are uncertain by applying a probabilistic value-based multi-criteria decision analysis (MCDA) method. Probability distributions were used to model random variation and parameter uncertainty in preferences, and parameter uncertainty in clinical outcomes. The posterior value distributions and rank probabilities for each treatment were obtained using Monte-Carlo simulations. The probability of achieving the first rank is the probability that a treatment represents the highest value to patients. We illustrated our methodology for a simplified case on six HIV treatments. Preferences were modeled with normal distributions and clinical outcomes were modeled with beta distributions. The treatment value distributions showed the rank order of treatments according to patients and illustrate the remaining decision uncertainty. This study demonstrated how patient preference data can be used to weigh clinical evidence using MCDA. The model takes into account uncertainty in preferences and clinical outcomes. The model can support decision makers during the aggregation step of the MCDA process and provides a first step toward preference-based personalized medicine, yet requires further testing regarding its appropriate use in real-world settings.

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

BACKGROUND: In response to 2012 guidance in which the US Food and Drug Administration's (FDA) Center for Devices and Radiological Health (CDRH) stated the importance of patient-centric measures in regulatory benefit-risk assessments, the Medical Device Innovation Consortium (MDIC) initiated a project. The project was used to develop a framework to help the Food and Drug Administration (FDA) and industry sponsors understand how patient preferences regarding benefit and risk might be integrated into the review of innovative medical devices. METHODS: A public-private partnership of experts from medical device industry, government, academia and non-profits collaborated on development of the MDIC patient centered benefit-risk framework. RESULTS: The MDIC Framework examines what patient preference information is and the potential use and value of patient preference information in the regulatory process and across the product development life cycle. The MDIC Framework also includes a catalog of patient preference assessment methods and an agenda for future research to advance the field. CONCLUSIONS: This article discusses key concepts in patient preference assessment of particular importance for regulators and researchers that are addressed in the MDIC Framework for patient centered benefit-risk assessment as well as the unique public-private collaboration that led its development.

The effect of information on preferences for treatments of metastatic renal cell carcinoma.

OBJECTIVE: Limited information exists regarding the effect of uncertainty in outcomes on patient preferences for metastatic renal cell carcinoma (mRCC) treatments. This study tested the effect on patients' preferences and willingness to tolerate toxicities when patients were provided with information about possible correlations between treatment-related toxicities and efficacy. RESEARCH DESIGN AND METHODS: Patients with self-reported RCC diagnosis completed an online survey. Respondents were randomly assigned to the information treatment (i.e. information about the possible correlation). Medicines were defined by progression-free survival (PFS), three toxicities potentially correlated with PFS, and one toxicity uncorrelated with PFS. Direct-elicitation questions measured willingness to tolerate the toxicities, preferences for medicines with higher toxicity but a higher chance of longer PFS, and preferences for medicines with higher toxicity during treatment and a 2 week dosing schedule break. A discrete-choice experiment (DCE) tested the effect of information on relative preferences for medication attributes. RESULTS: A total of 378 RCC patients completed the survey. Respondents who received the information reported greater willingness to accept more severe toxicities and preferred treatment with a higher chance of longer PFS but more severe toxicities. The DCE results were consistent with the hypothesis that the information increased willingness to tolerate toxicities; however, the results were only statistically significant for changes in fatigue (none to severe; p < 0.05) and hypertension (none to manageable; p < 0.05). LIMITATIONS: Online recruitment through patient support groups may limit generalizability to the population of patients with mRCC who would be candidates for the targeted therapies. CONCLUSIONS: The findings suggest that RCC patients have diverse preferences but may be willing to continue targeted therapies, even in the presence of severe toxicities, if there is a chance of improved clinical benefit. Physicians should provide patients with comprehensive information about medication features, including toxicities and efficacy (and their potential correlation), to improve compliance and optimize outcomes.

Statistical Methods for the Analysis of Discrete Choice Experiments: A Report of the ISPOR Conjoint Analysis Good Research Practices Task Force.

Conjoint analysis is a stated-preference survey method that can be used to elicit responses that reveal preferences, priorities, and the relative importance of individual features associated with health care interventions or services. Conjoint analysis methods, particularly discrete choice experiments (DCEs), have been increasingly used to quantify preferences of patients, caregivers, physicians, and other stakeholders. Recent consensus-based guidance on good research practices, including two recent task force reports from the International Society for Pharmacoeconomics and Outcomes Research, has aided in improving the quality of conjoint analyses and DCEs in outcomes research. Nevertheless, uncertainty regarding good research practices for the statistical analysis of data from DCEs persists. There are multiple methods for analyzing DCE data. Understanding the characteristics and appropriate use of different analysis methods is critical to conducting a well-designed DCE study. This report will assist researchers in evaluating and selecting among alternative approaches to conducting statistical analysis of DCE data. We first present a simplistic DCE example and a simple method for using the resulting data. We then present a pedagogical example of a DCE and one of the most common approaches to analyzing data from such a question format-conditional logit. We then describe some common alternative methods for analyzing these data and the strengths and weaknesses of each alternative. We present the ESTIMATE checklist, which includes a list of questions to consider when justifying the choice of analysis method, describing the analysis, and interpreting the results.

Stated Preference for Cancer Screening: A Systematic Review of the Literature, 1990-2013.

INTRODUCTION: Stated-preference methods provide a systematic approach to quantitatively assess the relative preferences for features of cancer screening tests. We reviewed stated-preference studies for breast, cervical, and colorectal cancer screening to identify the types of attributes included, the use of questions to assess uptake, and whether gaps exist in these areas. The goal of our review is to inform research on the design and promotion of public health programs to increase cancer screening. METHODS: Using the PubMed and EconLit databases, we identified studies published in English from January 1990 through July 2013 that measured preferences for breast, cervical, and colorectal cancer screening test attributes using conjoint analysis or a discrete-choice experiment. We extracted data on study characteristics and results. We categorized studies by whether attributes evaluated included screening test, health care delivery characteristics, or both. RESULTS: Twenty-two studies met the search criteria. Colorectal cancer was the most commonly studied cancer of the 3. Fifteen studies examined only screening test attributes (efficacy, process, test characteristics, and cost). Two studies included only health care delivery attributes (information provided, staff characteristics, waiting time, and distance to facility). Five studies examined both screening test and health care delivery attributes. Overall, cancer screening test attributes had a significant effect on a patient's selection of a cancer screening test, and health care delivery attributes had mixed effects on choice. CONCLUSION: A growing number of studies examine preferences for cancer screening tests. These studies consistently find that screening test attributes, such as efficacy, process, and cost, are significant determinants of choice. Fewer studies have examined the effect of health care delivery attributes on choice, and the results from these studies are mixed. There is a need for additional studies on the barriers to cancer screening uptake, including health care delivery attributes, and the effect of education materials on preferences.

Patient, Caregiver, and Nurse Preferences for Treatments for Bone Metastases from Solid Tumors.

BACKGROUND: Bone-targeted agents (BTAs) used for the prevention of skeletal-related events (SREs) associated with metastatic bone disease possess different attributes that factor into treatment decisions. OBJECTIVE: The aim of this study was to evaluate preferences of patients, caregivers, and nurses for features of BTAs used to prevent SREs in patients with a self-reported physician diagnosis of bone metastasis from solid tumors. METHODS: Patients (n = 187), primary caregivers (n = 197), or nurses (n = 196) completed a web-enabled discrete-choice experiment (10-question survey) in which they chose between pairs of hypothetical profiles of BTAs. Each profile was defined by six key treatment attributes, including efficacy and safety (two each) and route/frequency of administration and cost (one each). The relative importance of treatment attributes and levels was estimated. RESULTS: The most important treatment attribute for patients and nurses was out-of-pocket cost, and for caregivers, treatment-related risk of renal impairment. Risk of renal impairment was the second most important attribute for patients and nurses, while time until first SRE was the third most important attribute for all respondents. For nurses, risk of osteonecrosis of the jaw was least important, and for patients and caregivers, mode of administration was least important. LIMITATIONS: Respondents considered hypothetical medications; therefore, their decisions may not have the same consequences as actual decisions. CONCLUSIONS: The perspectives of patients, caregivers, and nurses are integral when making treatment decisions about BTAs to prevent SREs associated with solid tumors. Identifying the relative importance of attributes of BTAs will aid in the proper selection of therapy in this setting, which may improve patient outcomes.

A discrete-choice experiment to quantify patient preferences for frequency of glucagon-like peptide-1 receptor agonist injections in the treatment of type 2 diabetes.

OBJECTIVE: Understanding patients' preferences for attributes of injectable antihyperglycemic regimens may improve patient satisfaction and medication adherence. Our objective was to quantify the preferences of patients with type 2 diabetes mellitus (T2DM) for reducing the frequency of glucagon-like peptide-1 receptor agonist injections from once daily to once weekly. METHODS: A total of 643 respondents with a self-reported physician diagnosis of type 2 diabetes completed a web-based discrete-choice experiment survey. The sample included four prespecified subgroups: currently using exenatide once weekly (n = 150), liraglutide once daily (n = 153), insulin (but not exenatide once weekly or liraglutide) (n = 156), and no injectable treatment (n = 184). Device attributes included type of injection device, needle size and pain, injection frequency, refrigeration, and injection-site reactions. Random-parameters logit was used to estimate the relative impact of device attributes on treatment choice for each subgroup. RESULTS: In all subgroups, changing injection frequency from daily to weekly (independent of the effect of injection frequency on preferences for other attributes) was the most important predictor of treatment choice. Switching from a longer and thicker needle to a shorter and thinner needle and eliminating injection-site reactions were also statistically significant predictors of device choice (P < 0.05). Exenatide once weekly users and those not currently using injections were more likely to choose a treatment with characteristics similar to exenatide once weekly. CONCLUSIONS: The treatment attribute most important to patients choosing among hypothetical injectable treatments for T2DM was injection frequency: patients preferred weekly over daily injections. LIMITATIONS: The primary limitations of this study are that it included only a limited number of attributes that may not reflect the full complexity of patient choices, diagnosis was self-reported, and patients were recruited from an Internet panel and may not be representative of the T2DM patient population.

Estimating the value of medical treatments to patients using probabilistic multi criteria decision analysis.

BACKGROUND: Estimating the value of medical treatments to patients is an essential part of healthcare decision making, but is mostly done implicitly and without consulting patients. Multi criteria decision analysis (MCDA) has been proposed for the valuation task, while stated preference studies are increasingly used to measure patient preferences. In this study we propose a methodology for using stated preferences to weigh clinical evidence in an MCDA model that includes uncertainty in both patient preferences and clinical evidence explicitly. METHODS: A probabilistic MCDA model with an additive value function was developed and illustrated using a case on hypothetical treatments for depression. The patient-weighted values were approximated with Monte Carlo simulations and compared to expert-weighted results. Decision uncertainty was calculated as the probability of rank reversal for the first rank. Furthermore, scenario analyses were done to assess the relative impact of uncertainty in preferences and clinical evidence, and of assuming uniform preference distributions. RESULTS: The patient-weighted values for drug A, drug B, drug C, and placebo were 0.51 (95% CI: 0.48 to 0.54), 0.51 (95% CI: 0.48 to 0.54), 0.54 (0.49 to 0.58), and 0.15 (95% CI: 0.13 to 0.17), respectively. Drug C was the most preferred treatment and the rank reversal probability for first rank was 27%. This probability decreased to 18% when uncertainty in performances was not included and increased to 41% when uncertainty in criterion weights was not included. With uniform preference distributions, the first rank reversal probability increased to 61%. The expert-weighted values for drug A, drug B, drug C, and placebo were 0.67 (95% CI: 0.65 to 0.68), 0.57 (95% CI: 0.56 to 0.59), 0.67 (95% CI: 0.61 to 0.71), and 0.19 (95% CI: 0.17 to 0.21). The rank reversal probability for the first rank according to experts was 49%. CONCLUSIONS: Preferences elicited from patients can be used to weigh clinical evidence in a probabilistic MCDA model. The resulting treatment values can be contrasted to results from experts, and the impact of uncertainty can be quantified using rank probabilities. Future research should focus on integrating the model with regulatory decision frameworks and on including other types of uncertainty.

Psoriasis patients' willingness to accept side-effect risks for improved treatment efficacy.

BACKGROUND: Previous studies suggest that efficacy is more important than side-effect risks to psoriasis patients. However, those studies did not consider potentially fatal risks of biologic treatments. OBJECTIVE: To quantify the risks patients are willing to accept for improvements in psoriasis symptoms. METHODS: Adults with a self-reported physician diagnosis of psoriasis were recruited through the National Psoriasis Foundation. Using a discrete-choice experiment, patients completed a series of nine choice questions, each including a pair of hypothetical treatments. Treatments were defined by severity of plaques, body surface area (BSA), and 10-year risks of tuberculosis, serious infection and lymphoma. RESULTS: For complete clearance of 25% BSA with mild plaques, respondents (n = 1608) were willing to accept a 20% (95% confidence interval: 9-26%) risk of serious infection, 10% (5-15%) risk of tuberculosis and 2% (1-3%) risk of lymphoma. For complete clearance of 25% BSA with severe plaques, respondents were willing to accept a 54% (48-62%) risk of serious infection, 36% (28-49%) risk of tuberculosis and 8% (7-9%) risk of lymphoma. LIMITATIONS: Respondents were asked to evaluate hypothetical scenarios. Actual treatment choices may differ. CONCLUSION: Respondents were willing to accept risks above likely clinical exposures for improvements in psoriasis symptoms. Individual risk tolerances may vary.

Incorporating patient-preference evidence into regulatory decision making.

BACKGROUND: Patients have a unique role in deciding what treatments should be available for them and regulatory agencies should take their preferences into account when making treatment approval decisions. This is the first study designed to obtain quantitative patient-preference evidence to inform regulatory approval decisions by the Food and Drug Administration Center for Devices and Radiological Health. METHODS: Five-hundred and forty United States adults with body mass index (BMI) ≥ 30 kg/m(2) evaluated tradeoffs among effectiveness, safety, and other attributes of weight-loss devices in a scientific survey. Discrete-choice experiments were used to quantify the importance of safety, effectiveness, and other attributes of weight-loss devices to obese respondents. A tool based on these measures is being used to inform benefit-risk assessments for premarket approval of medical devices. RESULTS: Respondent choices yielded preference scores indicating their relative value for attributes of weight-loss devices in this study. We developed a tool to estimate the minimum weight loss acceptable by a patient to receive a device with a given risk profile and the maximum mortality risk tolerable in exchange for a given weight loss. For example, to accept a device with 0.01 % mortality risk, a risk tolerant patient will require about 10 % total body weight loss lasting 5 years. CONCLUSIONS: Patient preference evidence was used make regulatory decision making more patient-centered. In addition, we captured the heterogeneity of patient preferences allowing market approval of effective devices for risk tolerant patients. CDRH is using the study tool to define minimum clinical effectiveness to evaluate new weight-loss devices. The methods presented can be applied to a wide variety of medical products. This study supports the ongoing development of a guidance document on incorporating patient preferences into medical-device premarket approval decisions.

A survey of patient preferences for oral antihyperglycemic therapy in patients with type 2 diabetes mellitus.

INTRODUCTION: Previous research has demonstrated a correlation among patient preferences, dosing burden, and medication nonadherence, a well-recognized challenge in type 2 diabetes mellitus (T2DM). The objective of this study was to elicit preferences for alternative dosing regimens for oral antihyperglycemic therapies among patients with T2DM and to quantify differences in dosing preferences among patients with different characteristics. METHODS: Preferences for dosing of oral antihyperglycemic drugs (OAD) were evaluated by surveying patients with T2DM in the United States (US). Survey participants were adult US patients with T2DM who were taking no or only 1 OAD and no injectable therapies. Each patient completed a web-enabled discrete-choice experiment (DCE) including a series of 8 pairs of hypothetical OAD profiles. Each profile was defined by reductions in average glucose, dosing schedule (e.g., once-weekly, once-daily, or twice-daily dosing), chance of mild-to-moderate gastrointestinal side effects, frequency of hypoglycemia, weight change, incremental risk of congestive heart failure, and cost. Each participant also answered a direct question about dosing preference. Random-parameters logit was used to analyze the DCE data. Prespecified subgroups were analyzed. RESULTS: Of 2,262 patients invited to participate, 923 were included in the analysis (mean age 63 years, 45% male, 79% white). Reducing dosing frequency was statistically significantly important to patients; however, it was relatively less important than medication cost or clinical outcomes. On average, patients preferred once-weekly to once-daily dosing. Patients not currently taking an OAD had a stronger preference for once-weekly dosing than patients on treatment (P = 0.012). Patients younger than 45 years had a stronger preference for weekly dosing than older patients (P < 0.075). CONCLUSIONS: For younger patients and patients not currently on treatment, once-weekly dosing may provide additional incentive to initiate and adhere to antihyperglycemic treatment; however, additional research will be required to confirm this hypothesis.