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

OBJECTIVE: We aimed to empirically compare maximum acceptable risk results estimated using both a discrete choice experiment (DCE) and a probabilistic threshold technique (PTT). METHODS: Members of the UK general public (n = 982) completed an online survey including a DCE and a PTT (in random order) measuring their preferences for preventative treatment for rheumatoid arthritis. For the DCE, a Bayesian D-efficient design consisting of four blocks of 15 choice tasks was constructed including six attributes with varying levels. The PTT used identical risk and benefit attributes. For the DCE, a panel mixed-logit model was conducted, both mean and individual estimates were used to calculate maximum acceptable risk. For the PTT, interval regression was used to calculate maximum acceptable risk. Perceived complexity of the choice tasks and preference heterogeneity were investigated for both methods. RESULTS: Maximum acceptable risk confidence intervals of both methods overlapped for serious infection and serious side effects but not for mild side effects (maximum acceptable risk was 32.7 percent-points lower in the PTT). Although, both DCE and PTT tasks overall were considered easy or very easy to understand and answer, significantly more respondents rated the DCE choice tasks as easier to understand compared with those who rated the PTT as easier (7-percentage point difference; p < 0.05). CONCLUSIONS: Maximum acceptable risk estimate confidence intervals based on a DCE and a PTT overlapped for two out of the three included risk attributes. More respondents rated the DCE as easier to understand. This may suggest that the DCE is better suited in studies estimating maximum acceptable risk for multiple risk attributes of differing severity, while the PTT may be better suited when measuring heterogeneity in maximum acceptable risk estimates or when investigating one or more serious adverse events.

Preferences for preventive treatments for rheumatoid arthritis: discrete choice survey in the UK, Germany and Romania.

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.

Acceptable risks of treatments to prevent rheumatoid arthritis among first-degree relatives: demographic and psychological predictors of risk tolerance.

OBJECTIVES: To quantify tolerance to risks of preventive treatments among first-degree relatives (FDRs) of patients with rheumatoid arthritis (RA). METHODS: Preventive 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. RESULTS: 289 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%). CONCLUSIONS: Age, perceived chance of developing RA and perceived duration of RA were associated with tolerance to some risks of preventive RA therapy.

Treatment preferences for preventive interventions for rheumatoid arthritis: protocol of a mixed methods case study for the Innovative Medicines Initiative PREFER project.

INTRODUCTION: Amidst 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 ANALYSIS: This 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 DISSEMINATION: This 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.

The utility of real-world evidence for benefit-risk assessment, communication, and evaluation of pharmaceuticals: Case studies.

PURPOSE: In recent years, novel types of real-world evidence (RWE) have played a role in various decision-making processes relating to medicinal products, including regulatory approval, patient access, health technology assessment, safety monitoring, clinical use, and post-approval lifecycle management. We therefore reviewed the potential utility of RWE in the cycle of medicinal product benefit-risk (BR) assessment, communication/risk minimization and evaluation ("BRACE"). METHODS: A convenience sample of illustrative studies was drawn from the published literature and examined. Specifically, we examined the purpose for using RWE, the type of RWE used, its novelty and how it might be integrated with other data and activities of the BRACE cycle, and how it contributed to regulatory decision-making. RESULTS: Eight studies were selected with each illustrating a different activity in the BRACE cycle ranging from BR assessment in the preapproval setting, post-approval assessment of safety or effectiveness, communicating BR information to patients and healthcare professionals, and evaluating the effectiveness of risk minimization initiatives to support a positive BR balance. CONCLUSIONS: RWE has an important role in informing regulatory decision-making regarding the BR management of medicines. With increasing digitalization, facilitating data collection and stakeholder engagement in health, this role is only expected to expand in the future. To reach the full potential of RWE, both regulators and sponsors will need to be familiar with a range of existing and emerging methods for generating and analyzing such evidence appropriately and achieve convergence regarding how different types of RWE can best be used to inform BR management and decision-making.

Patient Perceptions of Unmet Medical Need in Rheumatoid Arthritis: A Cross-Sectional Survey in the USA.

INTRODUCTION: Many rheumatoid arthritis (RA) patients do not achieve their treatment goals and experience symptoms that affect psychosocial outcomes and daily activities. This study aimed to identify and quantify the unmet needs perceived by US patients with RA currently taking a disease-modifying antirheumatic drug (DMARD). METHODS: A cross-sectional, web-based survey was conducted with RA patients recruited through CreakyJoints, an online patient support community, and ArthritisPower®, an online patient research registry, from December 2017 to January 2018. Participant patients were aged ≥ 21 years, failed ≥ 1 DMARDs, and were receiving their current DMARD(s) for ≥ 6 months; they answered 50 questions about treatment history, RA symptoms, and flares and completed the Rheumatoid Arthritis Impact of Disease (RAID) questionnaire and the Treatment Satisfaction Questionnaire for Medication (TSQM). Treatment satisfaction was defined by a TSQM global satisfaction score ≥ 80. RESULTS: Of 415 patients screened, 258 (62%) were eligible and completed the survey; 87% were women, and 87% white, with mean (SD) age of 54.5 (11.4) years. A total of 232 patients (90%) had current or past biologic DMARD (bDMARD) use, with 67% currently on a bDMARD, 65% on ≥ 1 conventional synthetic DMARD, and 40% on methotrexate. Forty-three percent of patients reported daily/almost daily use of prescription pain medications, and 44% reported a current flare. Mean (SD) TSQM scores were 59 [20] for effectiveness, 59 [26] for side effects, 72 [18] for convenience, and 65 [21] for global satisfaction. The mean (SD) RAID overall score was 5.1 (2.0) on a 0-10 scale. Only 26% (67 patients) were satisfied with their RA treatment. Patients not satisfied with treatment reported higher RAID scores overall and by domain, and approximately half reported a current flare. CONCLUSIONS: Results from this real-world survey suggest that three-fourths of RA patients are not satisfied with treatments, which include bDMARDs. Patients continued to experience bothersome symptoms that impacted their daily activities and life. There remains a need for improved disease management among currently treated RA patients. FUNDING: Eli Lilly and Company (Indianapolis, IN, USA).

Implementation of Structured Benefit-Risk Assessments in Marketing Authorization Applications: Lessons Learned.

BACKGROUND: A recent publication from Eli Lilly and Company provided guidance on incorporation of a structured benefit-risk assessment framework into Section 2.5.6 of the Clinical Overview of marketing authorization applications. Because a template alone cannot deliver a judicious benefit-risk evaluation, the purpose of this manuscript is to present lessons learned and practical approaches that pharmaceutical companies (sponsors) can apply in developing holistic benefit risk assessments of medicinal products for their marketing authorization applications. METHODS: Benefit-risk scientists at Eli Lilly and Company facilitated use of a structured benefit-risk assessment in Section 2.5.6 of the Clinical Overview for a number of marketing authorization applications submitted to regulators between 2013 and the 2016. Based on our experiences in implementing the approach described in the publication by Wolka et al, we have identified commonalities that contributed to successful implementation. RESULTS: The 3 key learnings from the authors' experience are to (1) use a cross-functional team approach; (2) employ a process that lends to the objectivity and efficiency of benefit-risk assessments; and (3) leverage data visualizations for clear and concise communication of benefit-risk information. CONCLUSIONS: Sponsors can apply these approaches to incorporate benefit-risk assessments into their marketing authorization applications. Further shared learnings and benchmarking among the pharmaceutical industry will be necessary to further advance the science and practice of benefit-risk assessment.

Incorporation of a Benefit-Risk Assessment Framework Into the Clinical Overview of Marketing Authorization Applications.

BACKGROUND: The main responsibility of regulators and industry is to ensure the benefit-risk balance of pharmaceutical products is positive for the intended patient populations. In recent decades, regulators and industry have taken steps to systematize benefit-risk decision making related to marketing authorization applications through the use of structured benefit-risk assessment. METHODS: This manuscript presents an outline for a structured benefit-risk assessment that can be incorporated into Section 2.5.6 of the Clinical Overview to provide the basis for approval of pharmaceutical products in these regulatory submissions. RESULTS: The structured format presents the benefits and risks of a pharmaceutical product in the context of the medical need in the disease state, the benefits and risks of available pharmacologic and nonpharmacologic therapies, and the approach for mitigating the risks of the product under review. CONCLUSIONS: Ultimately, such an approach that lends further support to quality decision making would be beneficial to patients who would be treated with new pharmaceutical products.

Benefit-Risk Assessment, Communication, and Evaluation (BRACE) throughout the life cycle of therapeutic products: overall perspective and role of the pharmacoepidemiologist.

PURPOSE: Optimizing a therapeutic product's benefit-risk profile is an on-going process throughout the product's life cycle. Different, yet related, benefit-risk assessment strategies and frameworks are being developed by various regulatory agencies, industry groups, and stakeholders. This paper summarizes current best practices and discusses the role of the pharmacoepidemiologist in these activities, taking a life-cycle approach to integrated Benefit-Risk Assessment, Communication, and Evaluation (BRACE). METHODS: A review of the medical and regulatory literature was performed for the following steps involved in therapeutic benefit-risk optimization: benefit-risk evidence generation; data integration and analysis; decision making; regulatory and policy decision making; benefit-risk communication and risk minimization; and evaluation. Feedback from International Society for Pharmacoepidemiology members was solicited on the role of the pharmacoepidemiologist. The case example of natalizumab is provided to illustrate the cyclic nature of the benefit-risk optimization process. RESULTS: No single, globally adopted benefit-risk assessment process exists. The BRACE heuristic offers a way to clarify research needs and to promote best practices in a cyclic and integrated manner and highlight the critical importance of cross-disciplinary input. Its approach focuses on the integration of BRACE activities for risk minimization and optimization of the benefit-risk profile. CONCLUSION: The activities defined in the BRACE heuristic contribute to the optimization of the benefit-risk profile of therapeutic products in the clinical world at both the patient and population health level. With interdisciplinary collaboration, pharmacoepidemiologists are well suited for bringing in methodology expertise, relevant research, and public health perspectives into the BRACE process.