Adolescent and caregiver preferences for juvenile idiopathic arthritis treatment: a discrete-choice experiment

Respondent characteristics

In the US, the survey instrument was completed by 197 adolescent patients (of 235 invited to be screened for the survey, including 82 invited through email and online panel portals and 153 through referral from caregivers) and 207 caregivers (of 4,309 who accessed the survey and completed the screening questions; 556 of these individuals met the eligibility criteria and consented to participate). In the UK, the survey instrument was completed by 100 adolescent patients (of 120 invited to be screened for the survey, all recruited through referral from caregivers) and 200 caregivers (of 4,382 who accessed the survey and completed the screening questions) (Table 2). Among the 197 US adolescents, 117 identified as male (59.4%) and 154 identified as White (78.2%); the average age was approximately 15 years (range, 14–17 years). Among the 207 US caregivers, 145 identified as male (70.0%) and 163 identified as White (78.7%). The average age was approximately 38 years (range, 21–62 years), and the average age of the caregiver’s child was 12 years (range, 0–17 years). Among the 100 UK adolescents, 80 identified as male (80.0%) and 89 identified as White (89.0%); the average age was approximately 15 years (range, 14–17 years). Among the 200 UK caregivers, 144 identified as male (72.0%) and 167 identified as White (83.5%). The average age was approximately 39 years (range, 21–64 years), and the average age of the caregiver’s child was 12 years (range, 2–17 years).

Table 2 Demographic characteristics of the respondentsPreference weights and conditional relative importance of attributes

Figure 2 plots the mean preference-weight estimate for each attribute level for the 4 cohorts. The vertical bars around each preference weight represent the 95% confidence interval. Preference weights are relative to each other and do not have an absolute interpretation. The attribute levels with larger preference weights are preferred to attribute levels with smaller preference weights. Figure 3 displays the CRI for each attribute for the 4 cohorts.

Fig. 2figure 2

Random-Parameters Logit Model Estimates: Preference Weights. A US Adolescents (N = 197). B US Caregivers (N = 207). C UK Adolescents (N = 100). D UK Caregivers (N = 200). CI Confidence interval, DCE Discrete-choice experiment, IV Intravenous. Note: Attributes are presented in the order in which they appeared in the DCE questions. The vertical bars around each mean preference weight represent the 95% CI around the point estimate. Because all attribute levels are effects coded, the sum of preference weights across levels of an attribute equals 0. Within each attribute, a higher preference weight indicates that a level is more preferred. The change in utility associated with a change in the levels of each attribute is represented by the vertical distance between the preference weights for any 2 levels of that attribute. Larger differences between preference weights indicate that respondents viewed the change as having a relatively greater effect on overall utility. For example, looking at Fig. 2A, a change in improvement in symptom control from “very poor to poor” to “very poor to fair” yields a utility increase of 0.745 (− 0.310 − [− 1.054]), whereas an increase in the time until next flare-up from 1 to 5 months yields a smaller utility increase of 0.547 (− 0.091 − [− 0.456]). Although both changes yield positive utility increases, the change from “very poor to poor” to “very poor to fair” yields a change 1.36 times more important than the change from 1 month until next flare-up to 5 months until next flare-up (0.745 ÷ 0.547). Alternatively, a change from no stomachache, nausea, or vomiting to stomachache (but with no feelings of throwing up) yields a negative utility change of − 0.703 (− 0.011 − 0.692), whereas a change from no headaches caused by the medicine to having headaches caused from the medicine yields a negative utility change of − 0.666 (− 0.333 − 0.333)

Fig. 3figure 3

Random-Parameters Logit Model Estimates: Scaled Conditional Relative Attribute Importance. A US Adolescents (N = 197). B US Caregivers (N = 207). C UK Adolescents (N = 100). D UK Caregivers (N = 200). CI Confidence interval, DCE Discrete-choice experiment. Note: Attributes are presented in the order in which they appeared in the DCE questions. For each attribute, the conditional relative importance was computed as the difference between the preference weights on the most and the least preferred level. Once computed, the conditional relative importance estimates were rescaled so that their sum was equal to 100; therefore, each one can be interpreted as the proportion of utility that can be gained by improving one attribute from the least to the most preferred level relative to the maximum utility gained from improving all attributes from the least to the most preferred level. The standard errors and the 95% CI for the differences were calculated using the delta method. The 95% CI around the point estimate is represented by the black vertical bars on top of the blue bars. For example, looking at Fig. 3A, the largest CRI is improvement in symptom control, followed by stomachache, nausea, and throwing up; time until next flare-up; headaches; mode and frequency of administration; and need for combination therapy

US respondents

As shown in Fig. 2A and B, the preference weights for US adolescents and US caregivers were ordered as expected, with better outcomes being preferred to worse outcomes. On average, US adolescents and caregivers preferred better symptom control; greater time until the next flare-up; less stomachache, nausea, and vomiting; and fewer headaches. US adolescents and caregivers also were indifferent between a treatment with combination therapy and one without, and were generally indifferent across modes of administration, as can be seen by the lack of statistically significant differences between levels.

Among US adolescents, the largest CRI was improvement in symptom control, followed by stomachache, nausea, and vomiting; time until next flare-up; headaches; mode and frequency of administration; and need for combination therapy (Fig. 3A). The CRIs that were not statistically different from each other at the 95% confidence level were time until next flare-up and headaches (P = 0.270) and need for combination therapy and mode and frequency of administration (P = 0.703).

Among US caregivers, the largest CRI was improvement in symptom control, followed by time until next flare-up; headaches; stomachache, nausea, and vomiting; mode and frequency of administration; and need for combination therapies (Fig. 3B). However, the CRIs for improvement in symptom control and time until next flare-up were not statistically different from each other at the 95% confidence level (P = 0.106). Additionally, the CRIs for stomachache, nausea, and vomiting; headaches; and mode and frequency of administration were not statistically different from each other at the 95% confidence level.

UK respondents

As shown in Figs. 2C and 2D, the preference weights for UK adolescents and caregivers were ordered as expected, with better outcomes being preferred to worse outcomes. On average, adolescents and caregivers preferred better symptom control; less stomachache, nausea, and vomiting; and fewer headaches. They also preferred tablets/syrup and injections to intravenous (IV) infusions.

Among UK adolescents, although the difference in preference weights for a treatment with and without combination therapy was not statistically significant, adolescents appeared to prefer combination therapy (in which they received additional medicines, as opposed to no additional medicines) (Fig. 2C). Generally, there were few statistically significant differences across attribute levels, potentially due to sample size constraints. For example, there were not statistically significantly different preferences across the levels of time until next flare-up, and adolescents in the UK did not have statistically significantly different preferences between treatments by tablets and treatments by injections. Among UK adolescents, the most important attribute was headaches, followed by improvement in symptom control (Fig. 3C). However, the CRIs for headaches and improvement in symptom control were not statistically significantly different from each other (P = 0.819). Mode and frequency of administration and stomachache, nausea, and vomiting came next in order of importance. Time until next flare-up and the need for combination therapy were the 2 least important attributes, and the respective CRIs were not statistically significantly different from 0.

Like UK adolescents, UK caregivers preferred treatments that require combination therapy to those that do not require combination therapy (Fig. 2D). As with the UK adolescent sample, this could possibly be explained by previous experience with combination therapy or because the respondents interpreted having to take an additional medicine as an indicator of more efficacy. Among UK caregivers, the largest CRI was for symptom control, followed by headaches; stomachache, nausea, and vomiting; time until next flare-up; need for combination therapy; and mode and frequency of administration (Fig. 3D). The CRI for improvement in symptom control was statistically significantly different from the CRIs for all other attributes at the 95% confidence level. However, none of the CRIs were statistically significantly different from each other at the 95% confidence level for the other 5 attributes: time until next flare-up; stomachache, nausea, and vomiting; headaches; need for combination therapy; and mode and frequency of administration.

Subgroup analysis

Results of the subgroup analyses for the US cohorts revealed significant preference heterogeneity for adolescents across multiple sample characteristics but minimal preference heterogeneity for caregivers (Table 3 and Figures S1-S17, Supplemental Appendix A). Systematically different preferences were found in the US adolescent cohort among subgroups defined by gender, methotrexate experience, headache experience, and stomachache experience and in the US adult cohort only among the subgroup defined by the caregiver’s child’s experience with vomiting.

Table 3 Subgroup analysis, by cohort

For the UK cohorts, results of the subgroup analyses revealed a significant amount of preference heterogeneity across multiple sample characteristics for both adolescents and caregivers (Table 3 and Figures S18-S34, and Supplemental Appendix B). For the adolescent samples, systematically different preferences were found across subgroups defined by age, injection experience, headache experience, stomachache experience, and vomiting experience. For the caregiver samples, systematically different preferences were found across the subgroups defined by the age of the child, the gender of the child, the caregiver’s educational attainment, the child’s experience with methotrexate, the child’s experience with biologics, the child’s experience with headaches, the child’s experience with stomachaches, the child’s experience with vomiting, and the child’s experience with injections.

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