Search

Background When selecting samples for patient preference studies, it may be difficult or impractical to recruit participants who are eligible for a particular treatment decision. However, a general public sample may not be an appropriate proxy. Objective This study compares preferences for rheumatoid arthritis (RA) preventive treatments between members of the general public and first-degree relatives (FDRs) of confirmed RA patients to assess whether a sample of the general public can be used as a proxy for FDRs. Methods Participants were asked to imagine they were experiencing arthralgia and had screening tests indicating a 60% chance of developing RA within 2 yrs. Using a discrete choice experiment, participants were offered a series of choices between no treatment and 2 unlabeled hypothetical treatments to reduce the risk of RA. To assess data quality, time to complete survey sections and comprehension questions were assessed. A random parameter logit model was used to obtain attribute-level estimates, which were used to calculate relative importance, maximum acceptable risk (MAR), and market shares of hypothetical preventive treatments. Results The FDR sample (n = 298) spent more time completing the survey and performed better on comprehension questions compared with the general public sample (n = 982). The relative importance ranking was similar between the general public and FDR participant samples; however, other relative preference measures involving weights including MARs and market share differed between groups, with FDRs having numerically higher MARs. Conclusion In the context of RA prevention, the general public (average risk) may be a reasonable proxy for a more at-risk sample (FDRs) for overall relative importance ranking but not weights. The rationale for a proxy sample should be clearly justified. Highlights Participants from the general public were compared to first-degree relatives on their preferences for rheumatoid arthritis (RA) preventive treat, IMI-PREFER

Background: When selecting samples for patient preference studies, it may be difficult or impractical to recruit participants who are eligible for a particular treatment decision. However, a general public sample may not be an appropriate proxy. Objective: This study compares preferences for rheumatoid arthritis (RA) preventive treatments between members of the general public and first-degree relatives (FDRs) of confirmed RA patients to assess whether a sample of the general public can be used as a proxy for FDRs. Methods: Participants were asked to imagine they were experiencing arthralgia and had screening tests indicating a 60% chance of developing RA within 2 yrs. Using a discrete choice experiment, participants were offered a series of choices between no treatment and 2 unlabeled hypothetical treatments to reduce the risk of RA. To assess data quality, time to complete survey sections and comprehension questions were assessed. A random parameter logit model was used to obtain attribute-level estimates, which were used to calculate relative importance, maximum acceptable risk (MAR), and market shares of hypothetical preventive treatments. Results: The FDR sample (n = 298) spent more time completing the survey and performed better on comprehension questions compared with the general public sample (n = 982). The relative importance ranking was similar between the general public and FDR participant samples; however, other relative preference measures involving weights including MARs and market share differed between groups, with FDRs having numerically higher MARs.Conclusion: In the context of RA prevention, the general public (average risk) may be a reasonable proxy for a more at-risk sample (FDRs) for overall relative importance ranking but not weights. The rationale for a proxy sample should be clearly justified. Participants from the general public were compared

Objective: Some immunomodulatory drugs have been shown to delay the onset of, or lower the risk of developing, rheumatoid arthritis (RA), if given to individuals at risk. Several trials are ongoing in this area; however, little evidence is currently available about the views of those at risk of RA regarding preventive treatment.Method: Three focus groups and three interviews explored factors that are relevant to first degree relatives (FDRs) of RA patients and members of the general public when considering taking preventive treatment for RA. The semi-structured qualitative interview prompts explored participant responses to hypothetical attributes of preventive RA medicines. Transcripts of focus group/interview proceedings were inductively coded and analysed using a framework approach.Results: Twenty-one individuals (five FDRs, 16 members of the general public) took part in the study. Ten broad themes were identified describing factors that participants felt would influence their decisions about whether to take preventive treatment if they were at increased risk of RA. These related either directly to features of the specific treatment or to other factors, including personal characteristics, attitude towards taking medication, and an individual’s actual risk of developing RA.Conclusion: This research highlights the importance of non-treatment factors in the decision-making process around preventive treatments, and will inform recruitment to clinical trials as well as information to support shared decision making by those considering preventive treatment. Studies of treatment preferences in individuals with a confirmed high risk of RA would further inform clinical trial design., IMI-PREFER

Objective: Some immunomodulatory drugs have been shown to delay the onset of, or lower the risk of developing, rheumatoid arthritis (RA), if given to individuals at risk. Several trials are ongoing in this area; however, little evidence is currently available about the views of those at risk of RA regarding preventive treatment. Method: Three focus groups and three interviews explored factors that are relevant to first degree relatives (FDRs) of RA patients and members of the general public when considering taking preventive treatment for RA. The semi-structured qualitative interview prompts explored participant responses to hypothetical attributes of preventive RA medicines. Transcripts of focus group/interview proceedings were inductively coded and analysed using a framework approach. Results: Twenty-one individuals (five FDRs, 16 members of the general public) took part in the study. Ten broad themes were identified describing factors that participants felt would influence their decisions about whether to take preventive treatment if they were at increased risk of RA. These related either directly to features of the specific treatment or to other factors, including personal characteristics, attitude towards taking medication, and an individual’s actual risk of developing RA. Conclusion: This research highlights the importance of non-treatment factors in the decision-making process around preventive treatments, and will inform recruitment to clinical trials as well as information to support shared decision making by those considering preventive treatment. Studies of treatment preferences in individuals with a confirmed high risk of RA would further inform clinical trial design.

Patient preferences are gaining recognition among key stakeholders involved in benefit-risk decision-making along the medical product lifecycle. However, one of the main challenges of integrating patient preferences in benefit-risk decision-making is understanding differences in patient preference, which may be attributable to clinical characteristics (eg age, medical history) or psychosocial factors. Measuring the latter may provide valuable information to decision-makers but there is limited guidance regarding which psychological dimensions may influence patient preferences and which psychological instruments should be considered for inclusion in patient preference studies. This paper aims to provide such guidance by advancing evidence and consensus-based recommendations and considerations. Findings of a recent systematic review on psychological constructs having an impact on patients’ preferences and health-related decisions were expanded with input from an expert group (n = 11). These data were then used as the basis for final recommendations developed through two rounds of formal evaluation via an online Delphi consensus process involving international experts in the field of psychology, medical decision-making, and risk communication (n = 27). Three classes of recommendations emerged. Eleven psychological constructs reached consensus to be recommended for inclusion with the strongest consensus existing for health literacy, numeracy, illness perception and treatment-related beliefs. We also proposed a set of descriptive and check-list criteria to appraise available psychological measures to assist researchers and other stakeholders in including psychological assessment when planning patient preference studies. These recommendations can guide researchers and other stakeholders when designing and interpreting patient preference studies with a potential high impact in clinical practice and medical product benefit-risk decision-making processes.

Background: Research has been mainly focused on how to elicit patient preferences, with less attention on why patients form certain preferences. Objectives: To assess which psychological instruments are currently used and which psychological constructs are known to have an impact on patients' preferences and health-related decisions including the formation of preferences and preference heterogeneity. Methods: A systematic database search was undertaken to identify relevant studies. From the selected studies, the following information was extracted: study objectives, study population, design, psychological dimensions investigated, and instruments used to measure psychological variables. Results: Thirty-three studies were identified that described the association between a psychological construct, measured using a validated instrument, and patients' preferences or health-related decisions. We identified 33 psychological instruments and 18 constructs, and categorized the instruments into 5 groups, namely, motivational factors, cognitive factors, individual differences, emotion and mood, and health beliefs. Conclusions: This review provides an overview of the psychological factors and related instruments in the context of patients' preferences and decisions in healthcare settings. Our results indicate that measures of health literacy, numeracy, and locus of control have an impact on health-related preferences and decisions. Within the category of constructs that could explain preference and decision heterogeneity, health locus of control is a strong predictor of decisions in several healthcare contexts and is useful to consider when designing a patient preference study. Future research should continue to explore the association of psychological constructs with preference formation and heterogeneity to build on these initial recommendations.

Background: Preference assessments of patients with rheumatoid arthritis can support clinical therapeutic decisions for including biologic and targeted synthetic medicines to use. This study assesses patient preferences for attributes of second-line therapies and heterogeneity within these preferences to estimate the relative importance of treatment characteristics and to calculate the minimum benefit levels patients require to accept higher levels of side effects. Methods: Between November 2018 to August 2019, patients with rheumatoid arthritis were recruited to a survey containing demographic and disease-related questions as well as a discrete choice experiment to measure their preferences for second-line therapies using biologics or Janus kinases inhibitors. Treatment characteristics included were route of administration, frequency of use, probability of mild short-term side effects, probability of side effects changing appearance, probability of psychological side effects, probability of severe side effects and effectiveness of treatment. Results: A total of 358 patients were included in the analysis. A latent class analysis revealed three preference patterns: (1) treatment effectiveness as the single most important attribute, (2) route of administration as the most important attribute, closely followed by frequency of use and psychological side effects and (3) severe side effects as the most important attribute followed by psychological side effects. In addition, disease duration and mild side effects influenced the patients’ choices. Conclusion: Respondents found either effectiveness, route of administration or severe side effects as the most important attribute. Patients noting effectiveness as most important were more willing than other patients to accept higher risks of side effects.

Background: Research has been mainly focused on how to elicit patient preferences, with less attention on why patients form certain preferences. Objectives: To assess which psychological instruments are currently used and which psychological constructs are known to have an impact on patients' preferences and health-related decisions including the formation of preferences and preference heterogeneity. Methods: A systematic database search was undertaken to identify relevant studies. From the selected studies, the following information was extracted: study objectives, study population, design, psychological dimensions investigated, and instruments used to measure psychological variables. Results: Thirty-three studies were identified that described the association between a psychological construct, measured using a validated instrument, and patients' preferences or health-related decisions. We identified 33 psychological inst