Preferences for genetic interventions for SCA and Huntington’s disease: results of a discrete choice experiment among patients.

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Nienke J.H. Van Os, Mayke Oosterloo, Janneke P.C. Grutters, Brigitte A.B. Essers, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3576801/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Oct, 2024 Read the published version in Orphanet Journal of Rare Diseases → Version 1 posted 5 You are reading this latest preprint version Abstract Background Although genetic interventions are on the horizon for some polyglutamine expansion diseases, such as subtypes of spinocerebellar ataxia (SCA) and Huntington’s disease (HD), the patients’ preferences regarding these new therapies are unclear. This study aims to what extent different characteristics of genetic interventions affect the preferences of patients with SCA and HD with regard to these interventions. Methods Manifest and premanifest patients with SCA or HD were recruited online by platforms of patient associations. The respondents conducted a questionnaire that included a discrete choice experiment (DCE). The experimental design included 24 choice sets, but these were divided into three blocks of eight to reduce the number of tasks per respondent. Each choice set included two alternative treatments and consisted of four attributes (mode and frequency of administration, chance of a beneficial effect, risks, and follow-up), each with three or four different levels. The forced choice-elicitation format was used. Data were analyzed by using a multinominal logistic regression model. Results Responses of 216 participants were collected. The mode and frequency of administration of a genetic intervention, as well as the chance of a beneficial effect both influence the choice for a genetic intervention. Respondents less prefer repeated lumbar punctures compared to a single operation. As expected, a higher beneficial effect of treatment was preferred. Risks and follow-up did not influence the choice for a genetic intervention. Completing the DCE appeared difficult for some respondents, in particular for patients in a more severe disease stage of HD. Conclusions The results can be used for the design and implementation of future genetic interventional trials and care pathways for patients with rare movement disorders such as SCA and HD. INTRODUCTION Spinocerebellar ataxia (SCA) types 1, 2, 3, 6, 7, and 17, and Huntington’s disease (HD) are genetic neurodegenerative diseases caused by trinucleotide CAG repeat expansions in different disease-specific genes ( 1 , 2 ). Expansions of the polyglutamine (polyQ) tract in the disease-causing protein lead to a toxic gain-of-function. Although the underlying molecular mechanisms between SCA and HD overlap, the classic phenotype of both diseases differs. Patients with SCA develop a cerebellar syndrome, in some forms accompanied by non-ataxia features such as extrapyramidal movement disorders, polyneuropathy, ocular problems, spasticity, and cognitive decline ( 3 ). Patients with HD develop chorea, and psychiatric or behavioral problems with dementia ( 4 ). To date SCA and HD are both progressive and incurable, but new treatments for these diseases are being developed and clinically tested ( 5 – 7 ). Genetic interventions are promising, as they are designed to reduce levels of the mutant disease-causing protein by silencing transcriptional or modulating translational processes through micro-RNAs or antisense-oligonucleotides (AON) ( 8 ). As these agents cannot cross the blood-brain barrier, they need to be administered through repeated intrathecal or single intracerebral injections. At this moment, these therapies are being studied in different clinical phase 1 to 3 trials ( 6 , 9 – 12 ). The long-term benefits and possible risks for individual patients are not yet clear ( 13 ). Knowledge of the patients’ perspective on these therapies is of major relevance in patient-centered healthcare. Patient engagement can make important contributions to the customization of trial designs and clinical care pathways. In that way, patients are more satisfied en self-manageable ( 14 ), and compliance and success rates of new therapies can improve ( 15 ). In this study, we aimed to identify to what extent different characteristics of genetic interventions affect the preferences of patients with SCA and HD, and what the relative importance of these characteristics is. We used a discrete choice experiment (DCE), a method to quantify the strength of patients’ preferences regarding different aspects of a treatment. In a DCE, participants are requested to repeatedly choose between two hypothetical treatments, both with different characteristics ( 16 , 17 ). METHODS Discrete choice experiment A discrete choice experiment (DCE) was used, a technique that describes an intervention or therapy by its attributes like effectiveness, side effects or costs, and their levels. The combinations of different attributes and levels are used to characterize a number of hypothetical treatment choice sets. For every choice set, a participant is asked to choose the option they prefer ( 16 , 17 ). The aim is to establish which characteristics of genetic interventions influence choice behavior and which characteristics are preferred. For this study, the ISPOR guideline for conjoint analysis was used ( 18 ). Identification and selection of the attributes For the identification of the attributes, the following steps were taken. First, literature was reviewed for potentially relevant attributes related to genetic interventions for SCA and HD. A search in the PubMed database was performed in December 2021 and combined search terms for ‘genetic therapy’, with terms for ‘patient’, ‘perspectives’, and terms for SCA and HD. Since the search led to only two relevant results, the search was extended by also including studies of other neurodegenerative disorders. In total, four papers were eligible and data regarding different characteristics of genetic interventions were extracted in an Excel spreadsheet ( 19 – 22 ). Second, a list of possible relevant attributes was made by the first author, based on the results of the literature review. This list was discussed within the research team and consensus was reached about the attributes that were eligible for inclusion in the final list of topics (such as treatment goals and advantages, risks of procedures, treatment procedures, timing of treatment, and trial participation) for the semi-structured interviews with patients. The aim of the semi-structured interviews was to identify the most relevant attributes as seen by patients. Ten patients (five with HD and five with SCA; seven manifest, one early manifest and two premanifest) were recruited to participate in semi-structured interviews. All patients gave written informed consent. The interviews were guided by the list of attributes and were conducted by phone or video conference in December 2021 or January 2022. Since saturation was achieved at the end of the 10 interviews, no further interviews with other patients were planned. Detailed results of these interviews will be published separately. The list of attributes was discussed within the research team until consensus was reached. The final list included four attributes: ( 1 ) mode and frequency of administration, ( 2 ) chance of a beneficial effect, ( 3 ) risks, ( 4 ) and follow-up (see Table 1 ). Table 1 Attributes and levels included in the DCE. Attribute Level Explanation for the participant Mode and frequency of administration The way the drug enters the body and how many times the drug should be given. Single operation * You will be under general anesthesia (in a deep sleep) during the operation. The operation is one-time with a permanent effect. The drug is introduced into the brain through an injection. Lumbar puncture 12 times per year A lumbar puncture is an injection in the lower back. During this treatment you are awake and the skin can be made numb locally. A lumbar puncture has a temporary effect and must therefore be repeated every month. Lumbar puncture 6 times per year A lumbar puncture is an injection in the lower back. During this treatment you are awake and the skin can be made numb locally. A lumbar puncture has a temporary effect and must therefore be repeated every two months. Chance of a beneficial effect The number of people that experience a good result, such as slowing down disease progression. The exact chance is currently not known, therefore this chance is hypothetical. 20% 20 in 100 persons experienced a good result. 40% 40 in 100 persons experienced a good result. 60% 60 in 100 persons experienced a good result Risks The percentage of people that experience a negative side effect. 1% risk of infection, bleeding, paralysis * Short-term side effects that can arise immediately after the treatment. There is a 1% risk (1 in 100 persons) of side effects such as infection, bleeding, or even paralysis or death. These side effects can cause permanent damage. 10% risk of headache, pain at injection site Short-term side effects that can arise immediately after the treatment. There is a 10% (10 in 100 persons) risk of side effects such as headache or pain on the injection site. These side effects will pass. Unknown on long-term Long-term side effects that occur later, for example after years. The long-term side effects of genetic interventions are currently not known. It is also not known how likely these are to occur. Possible risks that can occur are for example undesirable effects of the injection of genetic material into the brain. Follow-up The healthcare provider and hospital that will conduct the follow-up appointments during the treatment period. Please note: this question is about follow-up appointments. A possible operation will always take place in the nationwide expert center for SCA or HD. Neurologist in local hospital without expertise * A neurologist who does not have specific knowledge of SCA or HD, working in the nearest local hospital. Neurologist in nearest university hospital without expertise A neurologist who does not have specific knowledge of SCA or HD, working in the nearest university hospital. Neurologist in nationwide expert center (University hospital) A neurologist who is familiar with SCA or HD, working in the nationwide expert center for SCA or HD. This is a university hospital. Nurse practitioner in nationwide expert center (University hospital) A nurse practitioner who is familiar with SCA or HD, working in the nationwide expert center for SCA or HD. This is a university hospital. * Level of the attribute which was used as the reference level for dummy coding. Selection of the levels For each attribute, levels and their descriptions were selected based on a review of the literature, information from ongoing clinical trials and from websites of pharmaceutical companies that are developing genetic interventions for SCA and HD. Since genetic interventions are not available yet for patients with SCA and HD, some levels were estimated based on the results of the semi-structured interviews and expert opinion of team members. Following the ISPOR guidelines, we did not use ranges to define attributes and we limited levels to three or four per attribute. Levels for the attribute ‘mode and frequency of administration’ were chosen based on genetic interventions that are currently being studied ( 6 ). Levels for the attribute ‘chance of a beneficial effect’ were chosen based on expert opinion and assumptions that came forward during the interviews with patients, where inclusion of outliers (i.e. extreme, unrealistic values) was avoided. Levels for the attribute ‘risks’ were chosen based on known side effects of lumbar punctures and intracerebral injections ( 23 ), and possible long-term effects were based on expert opinion. Levels of the attribute ‘follow-up’ were chosen based on logistic options within the healthcare system in the Netherlands (see Table 1 ). Experimental design and questionnaire Based on the number of attributes and levels, there are 3 3 x 4 1 = 108 hypothetical treatment combinations. For practical reasons, Ngene (version 1.1.1. http://www.choice-metrics.com ) was used to reduce this number to a manageable size by the development of an Bayesian efficient experimental design with 24 choice sets divided into three blocks of eight. Blocking was applied to reduce the number of tasks per respondent and thus cognitive burden. Full profiles were used which means that within each task, a respondent was presented all attributes that were included in the study. Profiles were grouped into sets of two per task (see Table 2 ). Respondents were randomly assigned to one of the three blocks, based on registration number. The forced choice-elicitation format was used. No opt-out or status-quo options were included, since no good alternative treatment is currently available for patients with SCA and HD. Each respondent was also given an additional choice set that checked for internal validity. This task included a within-set dominated pair (i.e. a choice set with alternative A is more desirable than alternative B for all attributes) ( 24 ), to check whether the respondents choose the dominated alternative within the choice set. A sensitivity analysis was done to check for the effect of excluding this choice set from the analysis. To improve the readability of the questionnaire, the text was screened and adapted by a communication expert of Radboud university medical center. A pilot test was conducted in 19 participants with SCA or HD, to check whether respondents understood the choice sets and explanations. The choice tasks were part of an online questionnaire that also included additional questions, such as questions about health status, sociodemographic information, and some contextual questions related to the choice tasks. The additional questions are listed in Supplement 1 . The questionnaire was built in the web-based survey tool LimeSurvey. Prior to the actual choice tasks, the questionnaire included a simple example question, in order to introduce the concepts of ‘attributes’ and ‘levels’ to the respondents. Furthermore, additional information, descriptions and explanations about the used attributes and levels was provided prior to the choice tasks and all participants had the option to read the explanation again at the moment the choice sets were presented. At the end of the choice sets, participants were asked how clear the questions were on a 5-point scale ranging from ‘very clear’ to ‘very unclear’, and how difficult it was for them to choose between the treatments in the choice sets, also on a 5-point scale ranging from ‘very easy’ to ‘very difficult’. Table 2 Example of a choice set in the DCE. Characteristics TREATMENT A TREATMENT B Mode and frequency of administration Lumbar puncture 6 times per year Single operation Chance of beneficial effect 20% (20 in 100 persons experienced a good result) 20% (20 in 100 persons experienced a good result) Risks 10% risk transient side effects as headache, pain at injection site Unknown on long-term Follow-up Nurse practitioner in nationwide expert center (university hospital) Neurologist in nearest university hospital without expertise Which option do you prefer? š š Data collection Data were collected between April 2022 and January 2023, with help of the Dutch patient associations for ataxia and HD. Adult patients with a confirmed diagnosis of SCA, HD or persons who carry a pathogenic CAG repeat expansion in a SCA or HD disease-causing gene were invited to participate. Respondents were recruited to complete the online questionnaire by placing a call with a link to the questionnaire on the patient organizations’ online media platforms, such as their websites, Facebook pages, and digital newsletters. Patients were sent a paper version of the questionnaire on request. All respondents were asked to give consent for the use of their anonymous responses before the questionnaire started. The Regional Ethics Committee Arnhem-Nijmegen, the Netherlands concluded that the Medical Research Involving Human Subjects Act (WMO) did not apply to this study (file number: 2021–9700). Based on the number of active members of the Dutch patient associations for SCA and HD, and based on prior respondent rates within these groups, it was estimated that it would be feasible to include 300 respondents, which is similar to the number that is recommended by others for robust quantitative analysis ( 25 ). Statistical analysis Descriptive data were analyzed with SPSS version 27 for Windows. The independent sample’s T test was used to compare means between two groups. Spearman’s rank correlation test was used to test whether ordinal variables correlated. A significance level of 0.05 was chosen for statistical significance. Discrete choice data were analyzed using Nlogit version 5 (Econometric Software, Inc.). A multinominal logit (MNL) model was used to estimate the effect of the attribute levels on preferences of the respondents. The four attributes were modeled as determinants for the decision for ‘treatment A’ or ‘treatment B’. The regression equation for this model is: U i = β 0 + β1 * lumbar puncture 6 times a year + β2 * lumbar puncture 12 times a year + β3 * beneficial effect + β4 * risk of 10% + β5 * unknown risk + β6 * follow-up nearest university hospital + β7 * follow-up nurse expert center + β8 * follow-up neurologist expert center + ε i Whereas U is the relative utility for a genetic intervention A or B, β0 is the constant, β1 to β8 are the specific attribute utility weights, and ε is an unobserved component or the error. The attribute levels of the attributes ‘mode and frequency of administration’, ‘risks’ and ‘follow-up’ were categorical variables and therefore, dummy coding was applied. ‘Single operation’, ‘risk of 1%’ and ‘follow-up in nearest local hospital’ were used as reference levels for the abovementioned attributes (see Table 1 ). ‘Chance of a beneficial effect’ was considered a continuous variable. A positive or negative sign indicates if a level is preferred or not preferred over the reference level. For the attribute ‘chance of a beneficial effect’, a positive sign was expected but for the other attributes, no a priori hypothesis was formulated. Model fit was assessed using log likelihood and McFadden’s pseudo R 2 . A constant term was included to check for left-to-right bias, which is a marker for a tendency to choose the first option in the choice task. To explore if preferences for specific attributes depend on the underlying disease (HD or SCA), interactions were added to the model. In addition, subgroup analyses were performed with the co-variate disease severity to examine if severity influenced preferences in these subgroups. To check for reliability of the results of the main model, a sensitivity analysis was conducted excluding the results of the choice set that checked for internal validity. Two subcategories for disease severity were established. SCA patients with no symptoms or who could still walk independently, and HD patients with disease stage 1 were classified as ‘mild’. SCA patients who needed a walking aid or wheelchair, and HD patients with disease stages 2 or higher were classified as ‘severe’. RESULTS Respondents characteristics The online questionnaire was started by 289 persons and completed by 214. Two respondents were excluded because they did not give informed consent for the use of their responses. Furthermore, four persons filled in a paper version of the questionnaire. In total, the results of 216 respondents were included. Characteristics of the respondents are summarized in Table 3 . Table 3 Respondent characteristics. N % Sex Male 108 / 216 50% Female 108 / 216 50% Disease SCA 115 / 216 53.2% HD 89 / 216 41.2% Other * 12 / 216 5.6% SCA subtype (n = 115) SCA1 9 / 115 7.8% SCA2 1 / 115 0.9% SCA3 58 / 115 50.4% SCA6 26 / 115 22.6% SCA7 1 / 115 0.9% SCA 8, 10, 12 or 36 2 / 115 1.7% Idiopathic late onset cerebellar ataxia 1 / 115 0.9% Other autosomal dominant cerebellar ataxia 9/ 115 7.8% Autosomal recessive cerebellar ataxia 0 / 115 0% No genetic testing 3 / 115 2.6% Other 5 / 115 4.3% SCA (and ‘others’) level of functioning 1 (35) (n = 127) No symptoms 15 / 127 11.8% Symptoms, walk independent 47 / 127 37% Symptoms, walk with walking aid 49 / 127 38.6% Symptoms, wheelchair bound 16 / 127 12.6% HD level of functioning 1 (36) (n = 89) Stage 1 (TFC-UHDRS 2 score 11–13) 49 / 89 55.1% Stage 2 (TFC-UHDRS score 7–10) 30 / 89 33.7% Stage 3 (TFC-UHDRS score 3–6) 10 / 89 11.2% Stage 4 (TFC-UHDRS score 1–2) 0 / 89 0% Stage 5 (severe disability) 0 / 89 0% Living situation Single 43 / 216 19.9% With child(ren) 5 / 216 2.3% With partner 107 / 216 49.5% With partner and child(ren) 58 / 216 26.9% With parents 2 / 216 0.9% Nursing home 1 / 216 0.5% Highest level of education Basic (ISCED-11 3 level 1–2) 31 / 216 14.4% Intermediate (ISCED-11 level 3–4) 78 / 216 36.1% Advanced (ISCED-11 level 5–8) 107 / 216 49.5% Most disabling symptom (SCA) (n = 115) Movement / coordination / walking 81 / 115 70.4% Speech 15 / 115 13% Fatigue / energy 10 / 115 8.7% Mood (depression) 1 / 115 0.9% Other 8 / 115 7% Most disabling symptom (HD) (n = 89) Movement / coordination / walking / chorea 28 / 89 31.5% Speech / swallowing 7 / 89 7.9% Memory / cognition 15 / 89 16.9% Behavioral changes 22 / 89 24.7% Mood (depression) 5 / 89 5.6% Other 12 / 89 13.5% Ideal timing of genetic intervention Before first symptoms 64 / 216 29.6% First symptoms 105 / 216 48.6% Need for walking aid 25 / 216 11.6% Unable to do job 8 / 216 3.7% Need for nursing home 7 / 216 3.2% Other 7 / 216 3.2% Wants to participate in trial Yes 173 / 216 80.1% No 43 / 216 19.9% Reason to participate in trial (n = 173) Earlier timing to receive treatment 43 / 173 24.9% Contribution to science 28 / 173 16.2% For future generations (children) 92 / 173 53.2% No costs 0 / 173 0% More follow-up 6 / 173 3.5% Other 4 / 173 2.3% Reason not to participate in trial (n = 43) Unknown risks 26 / 43 60.5% Chance of receiving placebo 3 / 43 7% Time 2 / 43 4.7% Travelling 6 / 43 14% Other 6 / 43 14% 1 For determination of the level of functioning, these 12 respondents were added to the ‘SCA’ subgroup. 2 TFC-UHDRS = Total Functional Capacity of the Unified Huntington Disease Rating Scale. 3 ISCED-11 = International Standard Classification of Education 20 Mean age of the respondents was 54.7 years (range 22–86 years, 2 with missing values). Twelve respondents filled in ‘other’ to the question which disease they had, however, of those 12 respondents, seven had a form of ataxia and one had premanifest HD. Three respondents had a genetic form of ataxia in their families and were asymptomatic, and one respondent had further unspecified ‘neurological symptoms’. The most common subtype of SCA was SCA3 (58 respondents) followed by SCA6 (26 respondents). A total of 111 respondents were categorized in a mild disease stage, and 105 respondents were categorized in a severe disease stage. For respondents with SCA and HD, the most disabling symptom was the problem with movement and coordination (n = 81 for SCA and n = 28 for HD), followed by behavioral changes in respondents with HD (n = 22). Out of 216 patients, 198 (91.7%) had a travelling time of two hours or less to the nearest nationwide expert center for SCA or HD. Opinions on timing and trials When respondents were asked what the ideal timing to start a genetic intervention was, most indicated that it would be the moment the first symptoms arise (n = 105; 48.6%), followed by starting treatment in the premanifest disease stage (n = 64; 29.6%). For respondents with SCA, the current disease stage positively correlated with the ideal timing of treatment, meaning that patients with a more advanced disease stage preferred a later start of genetic intervention as compared to patients with a less severe or premanifest disease stage (correlation coefficient 0.299; p < 0.001). For patients with HD, there was a similar trend but without statistical significance (p = 0.10) Eighty percent of respondents (n = 173) were willing to participate in a trial with genetic interventions. The most important reason for this decision was to gain knowledge for future generations (n = 92). Only 43 respondents said they would not participate in a trial with genetic interventions, mainly because of unknown risks (n = 26). Feasibility of the DCE On the question ‘how clear did you find the questions where you had to make a choice between the two treatments?’, most patients indicated that the choice sets were clear to read (score ‘very clear’ or ‘clear’; n = 193; 89.3%). However, on the question ‘did you find it difficult to make a choice between the two treatments or was it easy to choose for you?’ only 15.3% said the decisions were difficult to make, while 40.7% felt this was not easy/not difficult. Forty-three percent of respondents found it easy to make a decision (score ‘very easy’ and ‘easy’ n = 93). DCE choice task Results of the main effect model are shown in Table 4 . Table 4 Attribute preferences for all respondents and specified by disease. All respondents SCA HD β-coefficient Significance 95%CI β-coefficient significance 95%CI β-coefficient significance 95%CI Constant 0.032 NS -0.087; 0.152 -0.080 NS -0.233; 0.073 0.211 0.05 0.014; 0.408 Mode and frequency of administration Single operation Reference level Lumbar puncture 6 times a year -0.702 0.01 -0.871; -0.532 − .735 0.01 -0.954; -0.516 -0.675 0.01 -0.951; -0.400 Lumbar puncture 12 times a year -1.429 0.01 -1.606; -1.252 -1.358 0.01 -1.585; -1.130 -1.599 0.01 -1.893; -1.304 Chance of beneficial effect 0.072 0.01 0.064; 0.080 0.068 0.01 0.058; 0.078 0.079 0.01 0.066; 0.093 Risks 1% risk Reference level 10% risk -0.028 NS -0.195; 0.139 0.067 NS -0.147; 0.80 -0.169 NS -0.444; 0.106 Unknown long-term risk -0.089 NS -0.251; 0.072 0.119 NS -0.090; 0.328 -0.420 0.01 -0.683; -0.157 Follow-up Nearest local hospital Reference level Nearest university hospital -0.031 NS -0.248; 0.185 0.004 NS -0.272; 0.279 -0.084 NS -0.442; 0.274 Nurse expert center 0.164 NS -0.040; 0.369 0.196 NS -0.066; 0.458 -0.100 NS -0.235; 0.435 Neurologist expert center 0.043 NS -0.176; 0.261 0.112 NS -0.174; 0.397 -0.068 NS -0.414; 0.277 Log Likelihood -900.062 -542.891 -346.457 Chi squared 874.219 0.000 464.748 0.000 427.593 0.000 Adjusted pseudo R 2 0.32 AIC/N 0.935 0.973 0.878 Number of responders* 216 126 * 90 Number of observations 1944 1134 810 * The 12 respondents who filled in ‘’other underlying disease’’ were added to the SCA subgroup for statistical analysis, except for the premanifest HD patient. NS = not significant Two attributes, ‘mode and frequency of administration’ and ‘chance of a beneficial effect’ had a statistically significant impact on the respondents’ preference for a genetic intervention (p = 0.01). The attributes risks and follow-up were not of statistical significant influence on the decision of the total group of respondents. Respondents preferred lumbar punctures 6 and 12 times a year less compared to a single operation, given the negative β-coefficients of these two attribute levels (-0.702 and − 1.429, respectively, both with p = 0.01). As expected, respondents preferred a higher chance of a beneficial effect (coeffient: 0.072, p = 0.01). For the total group, the constant coefficient was not significant, meaning that there was no left to right bias in choosing the left versus right options. Differences between subgroups The interaction model showed that there was statistical significant interaction between the attribute level ‘unknown long-term risk’ (coefficient − 0.545; p = 0.01) and the covariate ‘underlying disorder’; meaning that the preference for this level of the attribute ‘risks’ depended on having SCA or HD as underlying disorder. The interaction model slightly improved model fit (likelihood ratio − 894.432 with pseudo R 2 0.33), and showed that respondents with HD statistical significantly prefer a 1% risk of possible permanent side-effects over unknown long-term risks (results not shown in tables). When performing an explorative analysis within the subgroups SCA and HD, adding the covariate disease severity to the model, it was shown that SCA patients with a mild disease severity prefer repeated lumbar punctures less compared to a single operation, a higher beneficial effect, and a 10% risk of transient side-effect over a 1% risk of possible permanent side-effects. Furthermore, they prefer follow-up with a nurse practitioner in an expert center over follow-up with a neurologist in the nearest local hospital. Patients with HD with mild disease severity prefer repeated lumbar punctures less compared to a single operation and a higher beneficial effect. Both SCA and HD patients in a severe disease stage preferred repeated lumbar punctures less compared to a single operation and a higher beneficial effect. In addition, HD patients with severe disease prefer a 1% risk of possible permanent side-effects over an unknown long-term risk. (see Table 5 ). Table 5 Attribute preferences, specified by disease and disease severity SCA – mild SCA – severe HD – mild HD – severe β-coefficient significance 95%CI β-coefficient significance 95%CI β-coefficient significance 95%CI β-coefficient significance 95%CI Constant -0.390 NS -0.278; 0.200 -0.120 NS -0.325; 0.084 0.018 NS -0.246; 0.281 0.459 0.01 0.149; 0.769 Mode and frequency of administration Single operation Reference level Lumbar puncture 6 times a year -0.860 0.01 -1.203; -0.517 -0.687 0.01 -0.976; -0.398 -0.618 0.01 -0.982; -0.253 -0.759 0.01 -1.192; -0.325 Lumbar puncture 12 times a year -1.610 0.01 -1.984; -1.235 -1.282 0.01 -1.582; -0.982 -1.481 0.01 -1.872; -1.089 -1.801 0.01 -2.267; -1.336 Chance of beneficial effect 0.091 0.01 0.073; 0.109 0.055 0.01 0.042; 0.068 0.085 0.01 0.067; 0.103 0.074 0.01 0.052; 0.096 Risks 1% risk Reference level 10% risk 0.340 0.05 0.000; 0.679 -0.070 NS -0.357; -0.216 -0.076 NS -0.443; 0.291 -0.309 NS -0.746; 0.129 Unknown long-term risk 0.267 NS -0.056; 0.590 0.050 NS -0.230; 0.329 -0.278 NS -0.625; 0.070 -0.623 0.01 -1.038; -0.209 Follow-up Nearest local hospital Reference level Nearest university hospital 0.339 NS -0.129; 0.806 -0.184 NS -0.539; 0.171 -0.273 NS -0.753; 0.206 0.116 NS -0.436; 0.668 Nurse expert center 0.472 0.05 0.057; 0.886 0.017 NS -0.333; 0.367 -0.121 NS -0.570; 0.328 0.380 NS -1.150; 0.909 Neurologist expert center 0.300 NS -0.146; 0.746 -0.006 NS -0.397; 0.385 -0.370 NS -0.844; 0.104 0.284 NS -0.240; 0.807 Log Likelihood -240.751 -297.604 -191.555 -147.709 Chi squared 282.208 0.000 203.959 0.000 235.156 0.000 203.547 0.000 AIC/N 0.895 1.048 0.891 0.871 Number of respondents * 62 65 49 40 Number of observations 558 585 450 360 * The 12 respondents who filled in ‘’other underlying disease’’ were added to the SCA subgroup for statistical analysis (for these patients the level of functioning was based on ref. Klockgether et al.) NS = not significant For respondents with HD, and especially those with severe symptoms, a strong left to right bias is seen, given the significance of the constants of 0.211 and 0.459, with p-values of 0.05 and 0.01, respectively, which indicates that they often chose the first (left) option. Additional analyses indeed showed that respondents with HD statistical significantly choose option A more frequently as compared to respondents with SCA (p = 0.012) Reliability Nine out of 216 respondents (4.2%) choose the non-dominant option in the choice set that tested for internal validity (i.e. the option that was less desirable than its alternative for all attributes). The other respondents (95.8%) choose the option the researchers would expect, namely the alternative with the best levels. Sensitivity analysis A sensitivity analysis excluding responses to the dominant choice set for all respondents showed no difference in the significance of the results of the main effect model (see Supplement 1 ). The likelihood ratio slightly improved to -854.612 with an adjusted pseudo R 2 of 0.36. In the interaction model, the significance level of ‘10% risk of transient side effects’ changed from 10–5%. In the subgroup analysis the constant in the model for patients with HD was not significant anymore. DISCUSSION In this study, a DCE quantified the preferences of patients with SCA or HD regarding genetic interventions. The results of this DCE show that mode and frequency of administration and chance of a beneficial effect influence the choice for a genetic intervention in patients with manifest or premanifest SCA or HD, and that preferences for certain attributes depend on the underlying disease and disease stage. This study includes the largest group of respondents in a DCE regarding genetic interventions to date, and is the first to get insight into the preferences of patients with SCA and HD. In 2021, Witkop et al. published the results of a DCE on preferences for gene therapy in patients with haemophilia. Interestingly, the haemophilia patients found the beneficial effect on bleeding rate the most important attribute, followed by dose frequency and durability ( 26 ), which is comparable to the results of this study. A recent DCE among patients with spinal muscular atrophy and their caregivers showed that improvement in current functioning was highly valued, and that oral medication and one-time infusion was strongly preferred over repeated intrathecal injections ( 27 ). In conclusion, all these DCE’s show that attributes reflecting the clinical effect and the administration process are considered important by patients. Two previous studies used a survey to get insight into SCA and HD patients’ preferences regarding genetic interventions in the hypothetical context of a clinical trial ( 19 , 20 ). These qualitative studies showed that patients are willing to undergo genetic interventions, and the potential benefit is a common motivation to participate in a trial with genetic interventions ( 20 ). However, the likelihood of patients with HD to enroll in a trial lowered in scenarios with more invasive surgical interventions ( 19 ), while respondents in the current study preferred a single operation over repeated lumbar punctures. Possibly, the contextual difference (clinical trial versus actual care) might be of influence here. Interestingly, the ideal timing for most patients was the moment the first symptoms arise, and not before the start of first symptoms. This is of major relevance as the HD and SCA field focus on the identification of premanifest carriers who are close to disease conversion – this stage is regarded as the optimal treatment window given that neuronal cell decline starts before the first clinical symptoms emerge ( 28 , 29 ). However, it is too preliminary to conclude on a possible divergence of patient versus academic perspective, as the ideal timing to start genetic interventions correlated with disease severity. Patients with a more severe disease stage preferred a later start compared to patients with a less severe or premanifest disease stage. This finding can result from a shift in the disease stage that is acceptable for someone with a disease, a phenomenon called ‘response shift’, which was also was observed in the semi-structured interviews. Limitations In general, this study included a complex DCE as this DCE included hypothetical scenarios and attributes with combined characteristics (i.e. the attribute ‘risks’ included a percentage and examples of side effects, the attribute ‘follow-up’ included a location and a level of expertise). Nevertheless, most respondents indicated they found the questions clear to read and not difficult to make a choice. The level of education of the respondents was high, as compared to the mean highest achieved level of education of the general population in the Netherlands, which is ISCED 3–4 ( 30 ). The web-based recruitment of respondents may have led to inclusion of more highly educated and mainly mildly affected respondents, as these persons might have better access to, and might be more active on the online platforms of patient associations. Furthermore, it is known that the cognitive burden of a DCE can reduce response rates ( 31 ), and this might be an additional explanation for a relative small proportion of lower educated and more severely affected respondents. Therefore, one should be cautious to extrapolate the results to the entire population of patients with SCA and HD. A high percentage of respondents indicated that they were willing to participate in a trial with genetic interventions. Selection bias might have also played a role here, as the respondents to our questionnaire are active on the online platforms of patient associations, a place where trials for new treatments are followed closely. In order to minimize the cognitive burden of the DCE, we minimized the number of attributes to four and the number of choice sets to eight. Nevertheless, the results show that patients with HD, and in particular patients with severe HD, tended to always choose the left alternative as the constant was significant. Normally, in an unlabeled design, the constant should be nonsignificant to assume that patients are considering all information in both alternatives and then choose the one that gives the highest utility. However, a significant constant indicates that respondents pay more attention to the information presented on the left and more often choose that alternative ( 32 ). The left-to-right bias might be due to the cognitive burden experienced by patients with HD, in particular those with severe symptoms, and should be kept in mind when designing future surveys or DCEs for this population. The fact that some of the results were non-significant suggested that these attributes were not relevant for the respondents’ decisions. Interestingly, the two attributes that always did reach significance were placed in the upper two rows of each choice task, and the nonsignificant attributes in the lowest two rows. For practical reasons and for the readability of the choice sets, randomization of the order of attributes was not applied. Possibly, the fact that people read from top to bottom may be of influence if respondents did not fully read the full choice task before making a choice: a phenomenon known as top-to-bottom bias ( 32 ). An explanation for the non-significance of the attribute ‘risk’ in the main analysis could be that this attribute was difficult to interpret for respondents as it included a combination of a chance and a certain severity; respondents could have ignored this attribute in their decision making. Because genetic interventions for SCA and HD are currently in the preclinical and first clinical trial phases, some of the chosen levels for the attributes ‘chance of a beneficial effect’ and ‘risk’ where chosen by the research team and not yet evidence-based. The results of clinical trials might show that chances of effect and risks might be different than here assumed, and this could subsequently result in other preferences and decisions of patients. Ninety-six percent of respondents choose the dominant option in the choice task that checked for internal validity. For the analysis, we decided to include the responses of the respondents who choose the non-dominant option to this choice task, as deleting responses can result in the removal of valid preferences ( 33 ). In addition, it can be questionable whether the ‘’irrational’’ responses of nine respondents who chose the non-dominant option were truly irrational or only deemed by the researchers to be worse. In that case, the learning process of the respondent or shortcomings in the study design can be held accountable for their choice ( 33 ). Overall, we decided to include the internal validity test in our main analysis because we considered the information from this choice sets still informative. However, we additionally performed sensitivity analysis to examine if results without the within dominance choice set were comparable, which turned out to be the case. Although the aimed number of 300 respondents was not reached, the number of 216 respondents can be considered sufficient for the analyses that were conducted. Unfortunately, there is no formal guidance on estimating the optimal sample size for DCE data although Louviere and Lancsar mention that one rarely requires more than 20 respondents per version to estimate reliable models ( 34 ). This means that for our study a minimum sample size of 60 respondents (3 versions of the questionnaire* 20 respondents) would be required. Taking into account that we also performed subgroup analysis, the number of 216 respondents can be considered sufficient. Implications for further scientific and clinical developments The results of this study may contribute to the design of future trials and future clinical care pathways. For example, patients seem to prefer a single surgical procedure over repeated lumbar punctures. This would require academia an industry to prioritize non-ASO interventions and/or alternative delivery. However, in the semi-structured interviews that were conducted in preparation of the DCE, patients who did not have had a lumbar puncture before seemed to be more hesitant than patients who did. Adequate information on lumbar punctures may improve the willingness to undergo these. Oral administration was not added as a treatment option in the current DCE. However, oral administration of genetic therapy is also being tested: A recent study on Branaplam (i.e. VIBRANT-HD; NCT05111249) was ended prematurely because of side effects. Unexpectedly, expertise did not seem to play a large role in the decision-making process as patients, except for the group with mild SCA, did not significantly prefer follow-up in an expert center over follow-up in the local hospital. In local hospitals, healthcare professionals generally do not have specific rare movement disorders expertise. We have not explored reasons for this preference of local hospital versus expert center. Patients with mild SCA did prefer follow-up in an expert center, which may be due to their better physical possibilities, as compared to patients with more severe SCA. Translating this into clinical practice, future care pathways might be organized in a way that patients, especially those in more advanced disease stages, can receive follow-up to further monitor the effect of new invasive genetic treatments in a local hospital. CONCLUSION This study shows that the frequency and mode of administration, and the chance of a beneficial effect are both of influence on the decision for a certain genetic intervention in patients with SCA and HD. Patients prefer repeated lumbar punctures ( 6 times or 12 times yearly) less compared to a single operation. The scientific versus patient perspective on the ideal timing of genetic interventions requires further study. These results provide guidance to design upcoming clinical trials and, if proven effective, future implementation of genetic interventions in care pathways. Declarations Ethical approval and consent to participate The study was approved by the Regional Committee on Research involving Human Subjects Arnhem-Nijmegen (file number: 2021-9700). Written informed consent was given by all participants. Consent for publication Not applicable. Availability of data and materials The dataset generated during this study are not publicly available due to privacy restrictions. Summaries are available upon reasonable request from the corresponding author. Competing interests Bart van de Warrenburg receives research support from NOW, ZonMw, Hersenstichting, Radboud university medical center, the Brugling Fonds, and Gossweiler Foundation. The authors have stated explicitly that there are no conflicts of interest in connection with this article. Funding This study was funded by the Academisch Alliantie Fonds (Radboudumc and Maastricht UMC+, the Netherlands). The funding source had no role in the preparation of data or the manuscript. Author’s Contributions NvO: conceptualization, data collection, data analysis, writing – original draft, writing review & editing. MO: conceptualization, writing review & editing, supervision. JG: conceptualization, writing review & editing, supervision. BE: conceptualization, data analysis, writing review & editing, supervision. BvdW: conceptualization, writing review & editing, supervision. All authors read and approved the final manuscript. Acknowledgement We thank Teije van Prooije for his help with recruiting the participants with SCA1 for the interviews. References A novel gene containing a trinucleotide repeat that is expanded and unstable on Huntington's disease chromosomes. The Huntington's Disease Collaborative Research Group. Cell. 1993;72(6):971-83. Verbeek DS, van de Warrenburg BP. Genetics of the dominant ataxias. Semin Neurol. 2011;31(5):461-9. Sullivan R, Yau WY, O'Connor E, Houlden H. Spinocerebellar ataxia: an update. J Neurol. 2019;266(2):533-44. McColgan P, Tabrizi SJ. Huntington's disease: a clinical review. Eur J Neurol. 2018;25(1):24-34. Tabrizi SJ, Estevez-Fraga C, van Roon-Mom WMC, Flower MD, Scahill RI, Wild EJ, et al. 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Orphanet J Rare Dis. 2022;17(1):1. Landrum Peay H, Fischer R, Tzeng JP, Hesterlee SE, Morris C, Strong Martin A, et al. Gene therapy as a potential therapeutic option for Duchenne muscular dystrophy: A qualitative preference study of patients and parents. PLoS One. 2019;14(5):e0213649. Paquin RS, Fischer R, Mansfield C, Mange B, Beaverson K, Ganot A, et al. Priorities when deciding on participation in early-phase gene therapy trials for Duchenne muscular dystrophy: a best-worst scaling experiment in caregivers and adult patients. Orphanet J Rare Dis. 2019;14(1):102. Evans RW. Complications of lumbar puncture. Neurol Clin. 1998;16(1):83-105. Johnson FR, Yang JC, Reed SD. The Internal Validity of Discrete Choice Experiment Data: A Testing Tool for Quantitative Assessments. Value Health. 2019;22(2):157-60. Orme B. Getting Started with Conjoint Analysis: Strategies for Product Design and Pricing Research. Chapter 7: Sample Size Issues for Conjoint Analysis. Madison, Wisconsin: Research Publishers LCC; 2019. Witkop M, Morgan G, O'Hara J, Recht M, Buckner TW, Nugent D, et al. Patient preferences and priorities for haemophilia gene therapy in the US: A discrete choice experiment. Haemophilia. 2021;27(5):769-82. Monnette A, Chen E, Hong D, Bazzano A, Dixon S, Arnold WD, et al. Treatment preference among patients with spinal muscular atrophy (SMA): a discrete choice experiment. Orphanet J Rare Dis. 2021;16(1):36. Tabrizi SJ, Scahill RI, Durr A, Roos RA, Leavitt BR, Jones R, et al. Biological and clinical changes in premanifest and early stage Huntington's disease in the TRACK-HD study: the 12-month longitudinal analysis. Lancet Neurol. 2011;10(1):31-42. Byrne LM, Rodrigues FB, Johnson EB, Wijeratne PA, De Vita E, Alexander DC, et al. Evaluation of mutant huntingtin and neurofilament proteins as potential markers in Huntington's disease. Sci Transl Med. 2018;10(458). 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The natural history of degenerative ataxia: a retrospective study in 466 patients. Brain. 1998;121 ( Pt 4):589-600. Unified Huntington's Disease Rating Scale: reliability and consistency. Huntington Study Group. Mov Disord. 1996;11(2):136-42. Supplementary Files supplement223okt2023.docx Cite Share Download PDF Status: Published Journal Publication published 28 Oct, 2024 Read the published version in Orphanet Journal of Rare Diseases → Version 1 posted Editorial decision: Minor revision 12 Feb, 2024 Reviewers agreed at journal 08 Jan, 2024 Reviewers invited by journal 08 Jan, 2024 Editor assigned by journal 10 Nov, 2023 First submitted to journal 08 Nov, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Van Os","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/UlEQVRIiWNgGAWjYDACZgYGxgYY5wOQswFIS4B57ERoYZyBooUZt0VwLcw8xGgxZ2c+9nBGBUNi/+zmw59t99jJbmfvMbzNm2PHYI5Di2UzW7rhhjMMiTPuHEuTznmWbLyz54yxNe+2ZKAUdi0Gh3nMJB+2MRgz3MgxY845wJy4AciQ5t12ACiFSwv/N8mH/xiM5W/kGH+2OFBPjBYeNsmNDQxyBjdyDKQZDhwmRgubmeSMYxJyhjfS0iR7DhwH+uVYseXcbck8OLWcP/xMsqfGhkfuRvLhDz8OVANDrHnjjbfb7OQMjjdg1wMBEphCPPjUj4JRMApGwSjADwA0dVwjiQcwIgAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0003-4266-7164","institution":"Radboud University Donders Institute for Brain Cognition and Behaviour: Radboud Universiteit Donders Institute for Brain Cognition and Behaviour","correspondingAuthor":true,"prefix":"","firstName":"Nienke","middleName":"J.H. Van","lastName":"Os","suffix":""},{"id":265959965,"identity":"92d7d7b7-c098-4bef-9097-9619aedaf219","order_by":1,"name":"Mayke Oosterloo","email":"","orcid":"","institution":"Maastricht University Medical Centre+ Neurology: Maastricht Universitair Medisch Centrum+ Neurologie","correspondingAuthor":false,"prefix":"","firstName":"Mayke","middleName":"","lastName":"Oosterloo","suffix":""},{"id":265959966,"identity":"f9fb0595-6f0b-4577-b86c-6312e1f7603a","order_by":2,"name":"Janneke P.C. Grutters","email":"","orcid":"","institution":"University Medical Center Nijmegen: Radboudumc","correspondingAuthor":false,"prefix":"","firstName":"Janneke","middleName":"P.C.","lastName":"Grutters","suffix":""},{"id":265959967,"identity":"bf590336-03a7-43fa-b088-d8fbec7103b9","order_by":3,"name":"Brigitte A.B. Essers","email":"","orcid":"","institution":"Maastricht University Medical Centre+: Maastricht Universitair Medisch Centrum+","correspondingAuthor":false,"prefix":"","firstName":"Brigitte","middleName":"A.B.","lastName":"Essers","suffix":""},{"id":265959968,"identity":"bc153b40-436e-4d93-b035-08f21e251c06","order_by":4,"name":"Bart P.C. van de Warrenburg","email":"","orcid":"","institution":"Radboud University Donders Institute for Brain Cognition and Behaviour: Radboud Universiteit Donders Institute for Brain Cognition and Behaviour","correspondingAuthor":false,"prefix":"","firstName":"Bart","middleName":"P.C. van","lastName":"de Warrenburg","suffix":""}],"badges":[],"createdAt":"2023-11-08 01:20:35","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3576801/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3576801/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13023-024-03408-2","type":"published","date":"2024-10-28T15:57:25+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":68206974,"identity":"e57d1ca1-8618-4c74-a66c-bce2daa237f9","added_by":"auto","created_at":"2024-11-04 16:34:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1125802,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3576801/v1/173acbdc-67e8-496a-b4c9-73a6c2cc7b22.pdf"},{"id":49426966,"identity":"8f92a56a-d4ca-4aa4-9851-3c2650de9600","added_by":"auto","created_at":"2024-01-10 15:58:19","extension":"docx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":16665,"visible":true,"origin":"","legend":"","description":"","filename":"supplement223okt2023.docx","url":"https://assets-eu.researchsquare.com/files/rs-3576801/v1/27acd7e11bd1e103340c3ec6.docx"}],"financialInterests":"","formattedTitle":"Preferences for genetic interventions for SCA and Huntington’s disease: results of a discrete choice experiment among patients.","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eSpinocerebellar ataxia (SCA) types 1, 2, 3, 6, 7, and 17, and Huntington\u0026rsquo;s disease (HD) are genetic neurodegenerative diseases caused by trinucleotide CAG repeat expansions in different disease-specific genes (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Expansions of the polyglutamine (polyQ) tract in the disease-causing protein lead to a toxic gain-of-function. Although the underlying molecular mechanisms between SCA and HD overlap, the classic phenotype of both diseases differs. Patients with SCA develop a cerebellar syndrome, in some forms accompanied by non-ataxia features such as extrapyramidal movement disorders, polyneuropathy, ocular problems, spasticity, and cognitive decline (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Patients with HD develop chorea, and psychiatric or behavioral problems with dementia (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo date SCA and HD are both progressive and incurable, but new treatments for these diseases are being developed and clinically tested (\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Genetic interventions are promising, as they are designed to reduce levels of the mutant disease-causing protein by silencing transcriptional or modulating translational processes through micro-RNAs or antisense-oligonucleotides (AON) (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). As these agents cannot cross the blood-brain barrier, they need to be administered through repeated intrathecal or single intracerebral injections. At this moment, these therapies are being studied in different clinical phase 1 to 3 trials (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan additionalcitationids=\"CR10 CR11\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). The long-term benefits and possible risks for individual patients are not yet clear (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eKnowledge of the patients\u0026rsquo; perspective on these therapies is of major relevance in patient-centered healthcare. Patient engagement can make important contributions to the customization of trial designs and clinical care pathways. In that way, patients are more satisfied en self-manageable (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), and compliance and success rates of new therapies can improve (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this study, we aimed to identify to what extent different characteristics of genetic interventions affect the preferences of patients with SCA and HD, and what the relative importance of these characteristics is. We used a discrete choice experiment (DCE), a method to quantify the strength of patients\u0026rsquo; preferences regarding different aspects of a treatment. In a DCE, participants are requested to repeatedly choose between two hypothetical treatments, both with different characteristics (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eDiscrete choice experiment\u003c/h2\u003e\n \u003cp\u003eA discrete choice experiment (DCE) was used, a technique that describes an intervention or therapy by its attributes like effectiveness, side effects or costs, and their levels. The combinations of different attributes and levels are used to characterize a number of hypothetical treatment choice sets. For every choice set, a participant is asked to choose the option they prefer (\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e). The aim is to establish which characteristics of genetic interventions influence choice behavior and which characteristics are preferred. For this study, the ISPOR guideline for conjoint analysis was used (\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003eIdentification and selection of the attributes\u003c/h2\u003e\n \u003cp\u003eFor the identification of the attributes, the following steps were taken. First, literature was reviewed for potentially relevant attributes related to genetic interventions for SCA and HD. A search in the PubMed database was performed in December 2021 and combined search terms for \u0026lsquo;genetic therapy\u0026rsquo;, with terms for \u0026lsquo;patient\u0026rsquo;, \u0026lsquo;perspectives\u0026rsquo;, and terms for SCA and HD. Since the search led to only two relevant results, the search was extended by also including studies of other neurodegenerative disorders. In total, four papers were eligible and data regarding different characteristics of genetic interventions were extracted in an Excel spreadsheet (\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eSecond, a list of possible relevant attributes was made by the first author, based on the results of the literature review. This list was discussed within the research team and consensus was reached about the attributes that were eligible for inclusion in the final list of topics (such as treatment goals and advantages, risks of procedures, treatment procedures, timing of treatment, and trial participation) for the semi-structured interviews with patients. The aim of the semi-structured interviews was to identify the most relevant attributes as seen by patients.\u003c/p\u003e\n \u003cp\u003eTen patients (five with HD and five with SCA; seven manifest, one early manifest and two premanifest) were recruited to participate in semi-structured interviews. All patients gave written informed consent. The interviews were guided by the list of attributes and were conducted by phone or video conference in December 2021 or January 2022. Since saturation was achieved at the end of the 10 interviews, no further interviews with other patients were planned. Detailed results of these interviews will be published separately.\u003c/p\u003e\n \u003cp\u003eThe list of attributes was discussed within the research team until consensus was reached. The final list included four attributes: (\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e) mode and frequency of administration, (\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e) chance of a beneficial effect, (\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e) risks, (\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e) and follow-up (see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAttributes and levels included in the DCE.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAttribute\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLevel\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eExplanation for the participant\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMode and frequency of administration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe way the drug enters the body and how many times the drug should be given.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle operation *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYou will be under general anesthesia (in a deep sleep) during the operation. The operation is one-time with a permanent effect. The drug is introduced into the brain through an injection.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLumbar puncture 12 times per year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eA lumbar puncture is an injection in the lower back. During this treatment you are awake and the skin can be made numb locally. A lumbar puncture has a temporary effect and must therefore be repeated every month.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLumbar puncture 6 times per year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eA lumbar puncture is an injection in the lower back. During this treatment you are awake and the skin can be made numb locally. A lumbar puncture has a temporary effect and must therefore be repeated every two months.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChance of a beneficial effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe number of people that experience a good result, such as slowing down disease progression. The exact chance is currently not known, therefore this chance is hypothetical.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 in 100 persons experienced a good result.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40 in 100 persons experienced a good result.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60 in 100 persons experienced a good result\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRisks\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe percentage of people that experience a negative side effect.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1% risk of infection, bleeding, paralysis *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eShort-term side effects that can arise immediately after the treatment. There is a 1% risk (1 in 100 persons) of side effects such as infection, bleeding, or even paralysis or death. These side effects can cause permanent damage.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10% risk of headache, pain at injection site\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eShort-term side effects that can arise immediately after the treatment. There is a 10% (10 in 100 persons) risk of side effects such as headache or pain on the injection site. These side effects will pass.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnknown on long-term\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLong-term side effects that occur later, for example after years. The long-term side effects of genetic interventions are currently not known. It is also not known how likely these are to occur. Possible risks that can occur are for example undesirable effects of the injection of genetic material into the brain.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFollow-up\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe healthcare provider and hospital that will conduct the follow-up appointments during the treatment period.\u003c/p\u003e\n \u003cp\u003ePlease note: this question is about follow-up appointments. A possible operation will always take place in the nationwide expert center for SCA or HD.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeurologist in local hospital without expertise *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eA neurologist who does not have specific knowledge of SCA or HD, working in the nearest local hospital.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeurologist in nearest university hospital without expertise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eA neurologist who does not have specific knowledge of SCA or HD, working in the nearest university hospital.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeurologist in nationwide expert center (University hospital)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eA neurologist who is familiar with SCA or HD, working in the nationwide expert center for SCA or HD. This is a university hospital.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNurse practitioner in nationwide expert center (University hospital)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eA nurse practitioner who is familiar with SCA or HD, working in the nationwide expert center for SCA or HD. This is a university hospital.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003e\u003csup\u003e*\u003c/sup\u003e Level of the attribute which was used as the reference level for dummy coding.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003eSelection of the levels\u003c/h2\u003e\n \u003cp\u003eFor each attribute, levels and their descriptions were selected based on a review of the literature, information from ongoing clinical trials and from websites of pharmaceutical companies that are developing genetic interventions for SCA and HD. Since genetic interventions are not available yet for patients with SCA and HD, some levels were estimated based on the results of the semi-structured interviews and expert opinion of team members. Following the ISPOR guidelines, we did not use ranges to define attributes and we limited levels to three or four per attribute.\u003c/p\u003e\n \u003cp\u003eLevels for the attribute \u0026lsquo;mode and frequency of administration\u0026rsquo; were chosen based on genetic interventions that are currently being studied (\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e). Levels for the attribute \u0026lsquo;chance of a beneficial effect\u0026rsquo; were chosen based on expert opinion and assumptions that came forward during the interviews with patients, where inclusion of outliers (i.e. extreme, unrealistic values) was avoided. Levels for the attribute \u0026lsquo;risks\u0026rsquo; were chosen based on known side effects of lumbar punctures and intracerebral injections (\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e), and possible long-term effects were based on expert opinion. Levels of the attribute \u0026lsquo;follow-up\u0026rsquo; were chosen based on logistic options within the healthcare system in the Netherlands (see Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003eExperimental design and questionnaire\u003c/h2\u003e\n \u003cp\u003eBased on the number of attributes and levels, there are 3\u003csup\u003e3\u003c/sup\u003e x 4\u003csup\u003e1\u003c/sup\u003e = 108 hypothetical treatment combinations. For practical reasons, \u003cem\u003eNgene\u003c/em\u003e (version 1.1.1. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.choice-metrics.com\u003c/span\u003e\u003c/span\u003e) was used to reduce this number to a manageable size by the development of an Bayesian efficient experimental design with 24 choice sets divided into three blocks of eight. Blocking was applied to reduce the number of tasks per respondent and thus cognitive burden.\u003c/p\u003e\n \u003cp\u003eFull profiles were used which means that within each task, a respondent was presented all attributes that were included in the study. Profiles were grouped into sets of two per task (see Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Respondents were randomly assigned to one of the three blocks, based on registration number.\u003c/p\u003e\n \u003cp\u003eThe forced choice-elicitation format was used. No opt-out or status-quo options were included, since no good alternative treatment is currently available for patients with SCA and HD.\u003c/p\u003e\n \u003cp\u003eEach respondent was also given an additional choice set that checked for internal validity. This task included a within-set dominated pair (i.e. a choice set with alternative A is more desirable than alternative B for all attributes) (\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e), to check whether the respondents choose the dominated alternative within the choice set. A sensitivity analysis was done to check for the effect of excluding this choice set from the analysis.\u003c/p\u003e\n \u003cp\u003eTo improve the readability of the questionnaire, the text was screened and adapted by a communication expert of Radboud university medical center. A pilot test was conducted in 19 participants with SCA or HD, to check whether respondents understood the choice sets and explanations.\u003c/p\u003e\n \u003cp\u003eThe choice tasks were part of an online questionnaire that also included additional questions, such as questions about health status, sociodemographic information, and some contextual questions related to the choice tasks. The additional questions are listed in \u003cem\u003eSupplement 1\u003c/em\u003e. The questionnaire was built in the web-based survey tool LimeSurvey.\u003c/p\u003e\n \u003cp\u003ePrior to the actual choice tasks, the questionnaire included a simple example question, in order to introduce the concepts of \u0026lsquo;attributes\u0026rsquo; and \u0026lsquo;levels\u0026rsquo; to the respondents. Furthermore, additional information, descriptions and explanations about the used attributes and levels was provided prior to the choice tasks and all participants had the option to read the explanation again at the moment the choice sets were presented.\u003c/p\u003e\n \u003cp\u003eAt the end of the choice sets, participants were asked how clear the questions were on a 5-point scale ranging from \u0026lsquo;very clear\u0026rsquo; to \u0026lsquo;very unclear\u0026rsquo;, and how difficult it was for them to choose between the treatments in the choice sets, also on a 5-point scale ranging from \u0026lsquo;very easy\u0026rsquo; to \u0026lsquo;very difficult\u0026rsquo;.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eExample of a choice set in the DCE.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTREATMENT A\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTREATMENT B\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMode and frequency of administration\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLumbar puncture 6 times per year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle operation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eChance of beneficial effect\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20% (20 in 100 persons experienced a good result)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20% (20 in 100 persons experienced a good result)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRisks\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10% risk transient side effects as headache, pain at injection site\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnknown on long-term\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFollow-up\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNurse practitioner in nationwide expert center (university hospital)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeurologist in nearest university hospital without expertise\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWhich option do you prefer?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026scaron;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026scaron;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003eData collection\u003c/h2\u003e\n \u003cp\u003eData were collected between April 2022 and January 2023, with help of the Dutch patient associations for ataxia and HD. Adult patients with a confirmed diagnosis of SCA, HD or persons who carry a pathogenic CAG repeat expansion in a SCA or HD disease-causing gene were invited to participate. Respondents were recruited to complete the online questionnaire by placing a call with a link to the questionnaire on the patient organizations\u0026rsquo; online media platforms, such as their websites, Facebook pages, and digital newsletters. Patients were sent a paper version of the questionnaire on request.\u003c/p\u003e\n \u003cp\u003eAll respondents were asked to give consent for the use of their anonymous responses before the questionnaire started.\u003c/p\u003e\n \u003cp\u003eThe Regional Ethics Committee Arnhem-Nijmegen, the Netherlands concluded that the Medical Research Involving Human Subjects Act (WMO) did not apply to this study (file number: 2021\u0026ndash;9700).\u003c/p\u003e\n \u003cp\u003eBased on the number of active members of the Dutch patient associations for SCA and HD, and based on prior respondent rates within these groups, it was estimated that it would be feasible to include 300 respondents, which is similar to the number that is recommended by others for robust quantitative analysis (\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eStatistical analysis\u003c/h2\u003e\n \u003cp\u003eDescriptive data were analyzed with SPSS version 27 for Windows. The independent sample\u0026rsquo;s T test was used to compare means between two groups. Spearman\u0026rsquo;s rank correlation test was used to test whether ordinal variables correlated. A significance level of 0.05 was chosen for statistical significance.\u003c/p\u003e\n \u003cp\u003eDiscrete choice data were analyzed using \u003cem\u003eNlogit\u003c/em\u003e version 5 (Econometric Software, Inc.).\u003c/p\u003e\n \u003cp\u003eA multinominal logit (MNL) model was used to estimate the effect of the attribute levels on preferences of the respondents. The four attributes were modeled as determinants for the decision for \u0026lsquo;treatment A\u0026rsquo; or \u0026lsquo;treatment B\u0026rsquo;. The regression equation for this model is:\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eU\u003c/em\u003e \u003csub\u003ei\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;\u0026beta;\u003csub\u003e0\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;\u0026beta;1 * lumbar puncture 6 times a year\u0026thinsp;+\u0026thinsp;\u0026beta;2 * lumbar puncture 12 times a year\u0026thinsp;+\u0026thinsp;\u0026beta;3 * beneficial effect\u0026thinsp;+\u0026thinsp;\u0026beta;4 * risk of 10% + \u0026beta;5 * unknown risk\u0026thinsp;+\u0026thinsp;\u0026beta;6 * follow-up nearest university hospital\u0026thinsp;+\u0026thinsp;\u0026beta;7 * follow-up nurse expert center\u0026thinsp;+\u0026thinsp;\u0026beta;8 * follow-up neurologist expert center\u0026thinsp;+\u0026thinsp;\u0026epsilon;\u003csub\u003ei\u003c/sub\u003e\u003c/p\u003e\n \u003cp\u003eWhereas \u003cem\u003eU\u003c/em\u003e is the relative utility for a genetic intervention A or B, \u0026beta;0 is the constant, \u0026beta;1 to \u0026beta;8 are the specific attribute utility weights, and \u0026epsilon; is an unobserved component or the error.\u003c/p\u003e\n \u003cp\u003eThe attribute levels of the attributes \u0026lsquo;mode and frequency of administration\u0026rsquo;, \u0026lsquo;risks\u0026rsquo; and \u0026lsquo;follow-up\u0026rsquo; were categorical variables and therefore, dummy coding was applied. \u0026lsquo;Single operation\u0026rsquo;, \u0026lsquo;risk of 1%\u0026rsquo; and \u0026lsquo;follow-up in nearest local hospital\u0026rsquo; were used as reference levels for the abovementioned attributes (see Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). \u0026lsquo;Chance of a beneficial effect\u0026rsquo; was considered a continuous variable. A positive or negative sign indicates if a level is preferred or not preferred over the reference level. For the attribute \u0026lsquo;chance of a beneficial effect\u0026rsquo;, a positive sign was expected but for the other attributes, no a priori hypothesis was formulated.\u003c/p\u003e\n \u003cp\u003eModel fit was assessed using log likelihood and McFadden\u0026rsquo;s pseudo R\u003csup\u003e2\u003c/sup\u003e. A constant term was included to check for left-to-right bias, which is a marker for a tendency to choose the first option in the choice task.\u003c/p\u003e\n \u003cp\u003eTo explore if preferences for specific attributes depend on the underlying disease (HD or SCA), interactions were added to the model. In addition, subgroup analyses were performed with the co-variate disease severity to examine if severity influenced preferences in these subgroups. To check for reliability of the results of the main model, a sensitivity analysis was conducted excluding the results of the choice set that checked for internal validity.\u003c/p\u003e\n \u003cp\u003eTwo subcategories for disease severity were established. SCA patients with no symptoms or who could still walk independently, and HD patients with disease stage 1 were classified as \u0026lsquo;mild\u0026rsquo;. SCA patients who needed a walking aid or wheelchair, and HD patients with disease stages 2 or higher were classified as \u0026lsquo;severe\u0026rsquo;.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003eRespondents characteristics\u003c/h2\u003e\n \u003cp\u003eThe online questionnaire was started by 289 persons and completed by 214. Two respondents were excluded because they did not give informed consent for the use of their responses. Furthermore, four persons filled in a paper version of the questionnaire. In total, the results of 216 respondents were included. Characteristics of the respondents are summarized in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e.\u0026nbsp;\u003c/p\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRespondent characteristics.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e108 / 216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e108 / 216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eDisease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e115 / 216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e89 / 216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 / 216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eSCA subtype (n\u0026thinsp;=\u0026thinsp;115)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSCA1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 / 115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSCA2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 / 115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSCA3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58 / 115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSCA6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26 / 115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSCA7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 / 115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSCA 8, 10, 12 or 36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 / 115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIdiopathic late onset cerebellar ataxia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 / 115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther autosomal dominant cerebellar ataxia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9/ 115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAutosomal recessive cerebellar ataxia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 / 115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo genetic testing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 / 115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 / 115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eSCA (and \u0026lsquo;others\u0026rsquo;) level of functioning\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/sup\u003e \u003cstrong\u003e(35) (n\u0026thinsp;=\u0026thinsp;127)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo symptoms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 / 127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSymptoms, walk independent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47 / 127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSymptoms, walk with walking aid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49 / 127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSymptoms, wheelchair bound\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 / 127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eHD level of functioning\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/sup\u003e \u003cstrong\u003e(36) (n\u0026thinsp;=\u0026thinsp;89)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStage 1 (TFC-UHDRS\u003csup\u003e2\u003c/sup\u003e score 11\u0026ndash;13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49 / 89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStage 2 (TFC-UHDRS score 7\u0026ndash;10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 / 89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStage 3 (TFC-UHDRS score 3\u0026ndash;6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 / 89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStage 4 (TFC-UHDRS score 1\u0026ndash;2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 / 89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStage 5 (severe disability)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 / 89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eLiving situation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43 / 216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWith child(ren)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 / 216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWith partner\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e107 / 216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWith partner and child(ren)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58 / 216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWith parents\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 / 216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNursing home\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 / 216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eHighest level of education\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBasic (ISCED-11\u003csup\u003e3\u003c/sup\u003e level 1\u0026ndash;2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31 / 216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIntermediate (ISCED-11 level 3\u0026ndash;4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e78 / 216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdvanced (ISCED-11 level 5\u0026ndash;8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e107 / 216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eMost disabling symptom (SCA) (n\u0026thinsp;=\u0026thinsp;115)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMovement / coordination / walking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e81 / 115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSpeech\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 / 115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFatigue / energy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 / 115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMood (depression)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 / 115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 / 115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eMost disabling symptom (HD) (n\u0026thinsp;=\u0026thinsp;89)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMovement / coordination / walking / chorea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 / 89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSpeech / swallowing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 / 89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMemory / cognition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 / 89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBehavioral changes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22 / 89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMood (depression)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 / 89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 / 89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eIdeal timing of genetic intervention\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBefore first symptoms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64 / 216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFirst symptoms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e105 / 216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeed for walking aid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25 / 216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnable to do job\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 / 216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeed for nursing home\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 / 216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 / 216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eWants to participate in trial\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e173 / 216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43 / 216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eReason to participate in trial (n\u0026thinsp;=\u0026thinsp;173)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEarlier timing to receive treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43 / 173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eContribution to science\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 / 173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFor future generations (children)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e92 / 173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo costs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 / 173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMore follow-up\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 / 173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 / 173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eReason not to participate in trial (n\u0026thinsp;=\u0026thinsp;43)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnknown risks\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26 / 43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChance of receiving placebo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 / 43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 / 43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTravelling\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 / 43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 / 43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003e\u003csup\u003e1\u003c/sup\u003e For determination of the level of functioning, these 12 respondents were added to the \u0026lsquo;SCA\u0026rsquo; subgroup.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003e\u003csup\u003e2\u003c/sup\u003e TFC-UHDRS\u0026thinsp;=\u0026thinsp;Total Functional Capacity of the Unified Huntington Disease Rating Scale.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003e\u003csup\u003e3\u003c/sup\u003e ISCED-11\u0026thinsp;=\u0026thinsp;International Standard Classification of Education 20\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003eMean age of the respondents was 54.7 years (range 22\u0026ndash;86 years, 2 with missing values). Twelve respondents filled in \u0026lsquo;other\u0026rsquo; to the question which disease they had, however, of those 12 respondents, seven had a form of ataxia and one had premanifest HD. Three respondents had a genetic form of ataxia in their families and were asymptomatic, and one respondent had further unspecified \u0026lsquo;neurological symptoms\u0026rsquo;. The most common subtype of SCA was SCA3 (58 respondents) followed by SCA6 (26 respondents).\u003c/p\u003e\n \u003cp\u003eA total of 111 respondents were categorized in a mild disease stage, and 105 respondents were categorized in a severe disease stage.\u003c/p\u003e\n \u003cp\u003eFor respondents with SCA and HD, the most disabling symptom was the problem with movement and coordination (n\u0026thinsp;=\u0026thinsp;81 for SCA and n\u0026thinsp;=\u0026thinsp;28 for HD), followed by behavioral changes in respondents with HD (n\u0026thinsp;=\u0026thinsp;22).\u003c/p\u003e\n \u003cp\u003eOut of 216 patients, 198 (91.7%) had a travelling time of two hours or less to the nearest nationwide expert center for SCA or HD.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eOpinions on timing and trials\u003c/h2\u003e\n \u003cp\u003eWhen respondents were asked what the ideal timing to start a genetic intervention was, most indicated that it would be the moment the first symptoms arise (n\u0026thinsp;=\u0026thinsp;105; 48.6%), followed by starting treatment in the premanifest disease stage (n\u0026thinsp;=\u0026thinsp;64; 29.6%). For respondents with SCA, the current disease stage positively correlated with the ideal timing of treatment, meaning that patients with a more advanced disease stage preferred a later start of genetic intervention as compared to patients with a less severe or premanifest disease stage (correlation coefficient 0.299; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). For patients with HD, there was a similar trend but without statistical significance (p\u0026thinsp;=\u0026thinsp;0.10)\u003c/p\u003e\n \u003cp\u003eEighty percent of respondents (n\u0026thinsp;=\u0026thinsp;173) were willing to participate in a trial with genetic interventions. The most important reason for this decision was to gain knowledge for future generations (n\u0026thinsp;=\u0026thinsp;92). Only 43 respondents said they would not participate in a trial with genetic interventions, mainly because of unknown risks (n\u0026thinsp;=\u0026thinsp;26).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eFeasibility of the DCE\u003c/h2\u003e\n \u003cp\u003eOn the question \u0026lsquo;how clear did you find the questions where you had to make a choice between the two treatments?\u0026rsquo;, most patients indicated that the choice sets were clear to read (score \u0026lsquo;very clear\u0026rsquo; or \u0026lsquo;clear\u0026rsquo;; n\u0026thinsp;=\u0026thinsp;193; 89.3%). However, on the question \u0026lsquo;did you find it difficult to make a choice between the two treatments or was it easy to choose for you?\u0026rsquo; only 15.3% said the decisions were difficult to make, while 40.7% felt this was not easy/not difficult. Forty-three percent of respondents found it easy to make a decision (score \u0026lsquo;very easy\u0026rsquo; and \u0026lsquo;easy\u0026rsquo; n\u0026thinsp;=\u0026thinsp;93).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eDCE choice task\u003c/h2\u003e\n \u003cp\u003eResults of the main effect model are shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAttribute preferences for all respondents and specified by disease.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eAll respondents\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eSCA\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eHD\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026beta;-coefficient\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSignificance\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e95%CI\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026beta;-coefficient\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003esignificance\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e95%CI\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026beta;-coefficient\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003esignificance\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e95%CI\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eConstant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.087; 0.152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.080\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.233; 0.073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.211\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.014; 0.408\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"10\"\u003e\n \u003cp\u003e\u003cstrong\u003eMode and frequency of administration\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle operation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"9\"\u003e\n \u003cp\u003eReference level\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLumbar puncture 6 times a year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.702\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.871; -0.532\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.735\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.954; -0.516\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.675\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.951; -0.400\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLumbar puncture 12 times a year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.429\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.606; -1.252\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.358\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.585; -1.130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.599\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.893; -1.304\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"10\"\u003e\n \u003cp\u003e\u003cstrong\u003eChance of beneficial effect\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.064; 0.080\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.058; 0.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.079\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.066; 0.093\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"10\"\u003e\n \u003cp\u003e\u003cstrong\u003eRisks\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1% risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"9\"\u003e\n \u003cp\u003eReference level\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10% risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.195; 0.139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.147; 0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.169\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.444; 0.106\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnknown long-term risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.089\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.251; 0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.090; 0.328\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.420\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.683; -0.157\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"10\"\u003e\n \u003cp\u003e\u003cstrong\u003eFollow-up\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNearest local hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"9\"\u003e\n \u003cp\u003eReference level\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNearest university hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.248; 0.185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.272; 0.279\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.084\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.442; 0.274\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNurse expert center\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.164\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.040; 0.369\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.196\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.066; 0.458\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.235; 0.435\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeurologist expert center\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.176; 0.261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.112\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.174; 0.397\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.414; 0.277\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLog Likelihood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-900.062\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-542.891\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-346.457\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChi squared\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e874.219\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e464.748\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e427.593\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdjusted pseudo R\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAIC/N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.935\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.973\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.878\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNumber of responders*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e126 *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNumber of observations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1944\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e810\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"10\"\u003e* The 12 respondents who filled in \u0026lsquo;\u0026rsquo;other underlying disease\u0026rsquo;\u0026rsquo; were added to the SCA subgroup for statistical analysis, except for the premanifest HD patient.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"10\"\u003eNS\u0026thinsp;=\u0026thinsp;not significant\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eTwo attributes, \u0026lsquo;mode and frequency of administration\u0026rsquo; and \u0026lsquo;chance of a beneficial effect\u0026rsquo; had a statistically significant impact on the respondents\u0026rsquo; preference for a genetic intervention (p\u0026thinsp;=\u0026thinsp;0.01). The attributes risks and follow-up were not of statistical significant influence on the decision of the total group of respondents.\u003c/p\u003e\n \u003cp\u003eRespondents preferred lumbar punctures 6 and 12 times a year less compared to a single operation, given the negative \u0026beta;-coefficients of these two attribute levels (-0.702 and \u0026minus;\u0026thinsp;1.429, respectively, both with p\u0026thinsp;=\u0026thinsp;0.01). As expected, respondents preferred a higher chance of a beneficial effect (coeffient: 0.072, p\u0026thinsp;=\u0026thinsp;0.01).\u003c/p\u003e\n \u003cp\u003eFor the total group, the constant coefficient was not significant, meaning that there was no left to right bias in choosing the left versus right options.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003eDifferences between subgroups\u003c/h2\u003e\n \u003cp\u003eThe interaction model showed that there was statistical significant interaction between the attribute level \u0026lsquo;unknown long-term risk\u0026rsquo; (coefficient \u0026minus;\u0026thinsp;0.545; p\u0026thinsp;=\u0026thinsp;0.01) and the covariate \u0026lsquo;underlying disorder\u0026rsquo;; meaning that the preference for this level of the attribute \u0026lsquo;risks\u0026rsquo; depended on having SCA or HD as underlying disorder. The interaction model slightly improved model fit (likelihood ratio \u0026minus;\u0026thinsp;894.432 with pseudo R\u003csup\u003e2\u003c/sup\u003e 0.33), and showed that respondents with HD statistical significantly prefer a 1% risk of possible permanent side-effects over unknown long-term risks (results not shown in tables).\u003c/p\u003e\n \u003cp\u003eWhen performing an explorative analysis within the subgroups SCA and HD, adding the covariate disease severity to the model, it was shown that SCA patients with a mild disease severity prefer repeated lumbar punctures less compared to a single operation, a higher beneficial effect, and a 10% risk of transient side-effect over a 1% risk of possible permanent side-effects. Furthermore, they prefer follow-up with a nurse practitioner in an expert center over follow-up with a neurologist in the nearest local hospital. Patients with HD with mild disease severity prefer repeated lumbar punctures less compared to a single operation and a higher beneficial effect.\u003c/p\u003e\n \u003cp\u003eBoth SCA and HD patients in a severe disease stage preferred repeated lumbar punctures less compared to a single operation and a higher beneficial effect. In addition, HD patients with severe disease prefer a 1% risk of possible permanent side-effects over an unknown long-term risk. (see Table \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAttribute preferences, specified by disease and disease severity\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eSCA \u0026ndash; mild\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eSCA \u0026ndash; severe\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eHD \u0026ndash; mild\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eHD \u0026ndash; severe\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026beta;-coefficient\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003esignificance\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e95%CI\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026beta;-coefficient\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003esignificance\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e95%CI\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026beta;-coefficient\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003esignificance\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e95%CI\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026beta;-coefficient\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003esignificance\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e95%CI\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eConstant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.390\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.278; 0.200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.325; 0.084\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.246; 0.281\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.459\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.149; 0.769\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"13\"\u003e\n \u003cp\u003e\u003cstrong\u003eMode and frequency of administration\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle operation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"12\"\u003e\n \u003cp\u003eReference level\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLumbar puncture 6 times a year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.860\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.203; -0.517\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.687\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.976; -0.398\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.618\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.982; -0.253\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.759\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.192; -0.325\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLumbar puncture 12 times a year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.610\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.984; -1.235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.282\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.582; -0.982\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.481\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.872; -1.089\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.801\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.267; -1.336\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"13\"\u003e\n \u003cp\u003e\u003cstrong\u003eChance of beneficial effect\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.073; 0.109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.042; 0.068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.067; 0.103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.052; 0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"13\"\u003e\n \u003cp\u003e\u003cstrong\u003eRisks\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1% risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"12\"\u003e\n \u003cp\u003eReference level\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10% risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.340\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.000; 0.679\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.357; -0.216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.076\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.443; 0.291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.309\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.746; 0.129\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnknown long-term risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.267\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.056; 0.590\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.230; 0.329\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.625; 0.070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.623\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.038; -0.209\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"13\"\u003e\n \u003cp\u003e\u003cstrong\u003eFollow-up\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNearest local hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"12\"\u003e\n \u003cp\u003eReference level\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNearest university hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.339\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.129; 0.806\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.539; 0.171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.273\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.753; 0.206\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.436; 0.668\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNurse expert center\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.472\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.057; 0.886\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.333; 0.367\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.570; 0.328\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.380\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.150; 0.909\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeurologist expert center\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.146; 0.746\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.397; 0.385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.370\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.844; 0.104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.284\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.240; 0.807\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLog Likelihood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-240.751\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-297.604\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-191.555\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-147.709\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChi squared\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e282.208\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e203.959\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e235.156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e203.547\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAIC/N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.895\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.891\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.871\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNumber of respondents *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNumber of observations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e558\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e585\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e450\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e360\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\"\u003e* The 12 respondents who filled in \u0026lsquo;\u0026rsquo;other underlying disease\u0026rsquo;\u0026rsquo; were added to the SCA subgroup for statistical analysis (for these patients the level of functioning was based on ref. Klockgether et al.)\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\"\u003eNS\u0026thinsp;=\u0026thinsp;not significant\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eFor respondents with HD, and especially those with severe symptoms, a strong left to right bias is seen, given the significance of the constants of 0.211 and 0.459, with p-values of 0.05 and 0.01, respectively, which indicates that they often chose the first (left) option. Additional analyses indeed showed that respondents with HD statistical significantly choose option A more frequently as compared to respondents with SCA (p\u0026thinsp;=\u0026thinsp;0.012)\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003eReliability\u003c/h2\u003e\n \u003cp\u003eNine out of 216 respondents (4.2%) choose the non-dominant option in the choice set that tested for internal validity (i.e. the option that was less desirable than its alternative for all attributes). The other respondents (95.8%) choose the option the researchers would expect, namely the alternative with the best levels.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003eSensitivity analysis\u003c/h2\u003e\n \u003cp\u003eA sensitivity analysis excluding responses to the dominant choice set for all respondents showed no difference in the significance of the results of the main effect model (see \u003cem\u003eSupplement 1\u003c/em\u003e). The likelihood ratio slightly improved to -854.612 with an adjusted pseudo R\u003csup\u003e2\u003c/sup\u003e of 0.36. In the interaction model, the significance level of \u0026lsquo;10% risk of transient side effects\u0026rsquo; changed from 10\u0026ndash;5%. In the subgroup analysis the constant in the model for patients with HD was not significant anymore.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn this study, a DCE quantified the preferences of patients with SCA or HD regarding genetic interventions. The results of this DCE show that mode and frequency of administration and chance of a beneficial effect influence the choice for a genetic intervention in patients with manifest or premanifest SCA or HD, and that preferences for certain attributes depend on the underlying disease and disease stage.\u003c/p\u003e \u003cp\u003eThis study includes the largest group of respondents in a DCE regarding genetic interventions to date, and is the first to get insight into the preferences of patients with SCA and HD. In 2021, Witkop et al. published the results of a DCE on preferences for gene therapy in patients with haemophilia. Interestingly, the haemophilia patients found the beneficial effect on bleeding rate the most important attribute, followed by dose frequency and durability (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), which is comparable to the results of this study. A recent DCE among patients with spinal muscular atrophy and their caregivers showed that improvement in current functioning was highly valued, and that oral medication and one-time infusion was strongly preferred over repeated intrathecal injections (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). In conclusion, all these DCE\u0026rsquo;s show that attributes reflecting the clinical effect and the administration process are considered important by patients.\u003c/p\u003e \u003cp\u003eTwo previous studies used a survey to get insight into SCA and HD patients\u0026rsquo; preferences regarding genetic interventions in the hypothetical context of a clinical trial (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). These qualitative studies showed that patients are willing to undergo genetic interventions, and the potential benefit is a common motivation to participate in a trial with genetic interventions (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). However, the likelihood of patients with HD to enroll in a trial lowered in scenarios with more invasive surgical interventions (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e), while respondents in the current study preferred a single operation over repeated lumbar punctures. Possibly, the contextual difference (clinical trial versus actual care) might be of influence here.\u003c/p\u003e \u003cp\u003eInterestingly, the ideal timing for most patients was the moment the first symptoms arise, and not before the start of first symptoms. This is of major relevance as the HD and SCA field focus on the identification of premanifest carriers who are close to disease conversion \u0026ndash; this stage is regarded as the optimal treatment window given that neuronal cell decline starts before the first clinical symptoms emerge (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). However, it is too preliminary to conclude on a possible divergence of patient versus academic perspective, as the ideal timing to start genetic interventions correlated with disease severity. Patients with a more severe disease stage preferred a later start compared to patients with a less severe or premanifest disease stage. This finding can result from a shift in the disease stage that is acceptable for someone with a disease, a phenomenon called \u0026lsquo;response shift\u0026rsquo;, which was also was observed in the semi-structured interviews.\u003c/p\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eIn general, this study included a complex DCE as this DCE included hypothetical scenarios and attributes with combined characteristics (i.e. the attribute \u0026lsquo;risks\u0026rsquo; included a percentage and examples of side effects, the attribute \u0026lsquo;follow-up\u0026rsquo; included a location and a level of expertise). Nevertheless, most respondents indicated they found the questions clear to read and not difficult to make a choice.\u003c/p\u003e \u003cp\u003eThe level of education of the respondents was high, as compared to the mean highest achieved level of education of the general population in the Netherlands, which is ISCED 3\u0026ndash;4 (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). The web-based recruitment of respondents may have led to inclusion of more highly educated and mainly mildly affected respondents, as these persons might have better access to, and might be more active on the online platforms of patient associations. Furthermore, it is known that the cognitive burden of a DCE can reduce response rates (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e), and this might be an additional explanation for a relative small proportion of lower educated and more severely affected respondents. Therefore, one should be cautious to extrapolate the results to the entire population of patients with SCA and HD.\u003c/p\u003e \u003cp\u003eA high percentage of respondents indicated that they were willing to participate in a trial with genetic interventions. Selection bias might have also played a role here, as the respondents to our questionnaire are active on the online platforms of patient associations, a place where trials for new treatments are followed closely.\u003c/p\u003e \u003cp\u003eIn order to minimize the cognitive burden of the DCE, we minimized the number of attributes to four and the number of choice sets to eight. Nevertheless, the results show that patients with HD, and in particular patients with severe HD, tended to always choose the left alternative as the constant was significant. Normally, in an unlabeled design, the constant should be nonsignificant to assume that patients are considering all information in both alternatives and then choose the one that gives the highest utility. However, a significant constant indicates that respondents pay more attention to the information presented on the left and more often choose that alternative (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). The left-to-right bias might be due to the cognitive burden experienced by patients with HD, in particular those with severe symptoms, and should be kept in mind when designing future surveys or DCEs for this population.\u003c/p\u003e \u003cp\u003eThe fact that some of the results were non-significant suggested that these attributes were not relevant for the respondents\u0026rsquo; decisions. Interestingly, the two attributes that always did reach significance were placed in the upper two rows of each choice task, and the nonsignificant attributes in the lowest two rows. For practical reasons and for the readability of the choice sets, randomization of the order of attributes was not applied. Possibly, the fact that people read from top to bottom may be of influence if respondents did not fully read the full choice task before making a choice: a phenomenon known as top-to-bottom bias (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). An explanation for the non-significance of the attribute \u0026lsquo;risk\u0026rsquo; in the main analysis could be that this attribute was difficult to interpret for respondents as it included a combination of a chance and a certain severity; respondents could have ignored this attribute in their decision making.\u003c/p\u003e \u003cp\u003eBecause genetic interventions for SCA and HD are currently in the preclinical and first clinical trial phases, some of the chosen levels for the attributes \u0026lsquo;chance of a beneficial effect\u0026rsquo; and \u0026lsquo;risk\u0026rsquo; where chosen by the research team and not yet evidence-based. The results of clinical trials might show that chances of effect and risks might be different than here assumed, and this could subsequently result in other preferences and decisions of patients.\u003c/p\u003e \u003cp\u003eNinety-six percent of respondents choose the dominant option in the choice task that checked for internal validity. For the analysis, we decided to include the responses of the respondents who choose the non-dominant option to this choice task, as deleting responses can result in the removal of valid preferences (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). In addition, it can be questionable whether the \u0026lsquo;\u0026rsquo;irrational\u0026rsquo;\u0026rsquo; responses of nine respondents who chose the non-dominant option were truly irrational or only deemed by the researchers to be worse. In that case, the learning process of the respondent or shortcomings in the study design can be held accountable for their choice (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Overall, we decided to include the internal validity test in our main analysis because we considered the information from this choice sets still informative. However, we additionally performed sensitivity analysis to examine if results without the within dominance choice set were comparable, which turned out to be the case.\u003c/p\u003e \u003cp\u003eAlthough the aimed number of 300 respondents was not reached, the number of 216 respondents can be considered sufficient for the analyses that were conducted. Unfortunately, there is no formal guidance on estimating the optimal sample size for DCE data although Louviere and Lancsar mention that one rarely requires more than 20 respondents per version to estimate reliable models (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). This means that for our study a minimum sample size of 60 respondents (3 versions of the questionnaire* 20 respondents) would be required. Taking into account that we also performed subgroup analysis, the number of 216 respondents can be considered sufficient.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eImplications for further scientific and clinical developments\u003c/h2\u003e \u003cp\u003eThe results of this study may contribute to the design of future trials and future clinical care pathways. For example, patients seem to prefer a single surgical procedure over repeated lumbar punctures. This would require academia an industry to prioritize non-ASO interventions and/or alternative delivery. However, in the semi-structured interviews that were conducted in preparation of the DCE, patients who did not have had a lumbar puncture before seemed to be more hesitant than patients who did. Adequate information on lumbar punctures may improve the willingness to undergo these. Oral administration was not added as a treatment option in the current DCE. However, oral administration of genetic therapy is also being tested: A recent study on Branaplam (i.e. VIBRANT-HD; NCT05111249) was ended prematurely because of side effects.\u003c/p\u003e \u003cp\u003eUnexpectedly, expertise did not seem to play a large role in the decision-making process as patients, except for the group with mild SCA, did not significantly prefer follow-up in an expert center over follow-up in the local hospital. In local hospitals, healthcare professionals generally do not have specific rare movement disorders expertise. We have not explored reasons for this preference of local hospital versus expert center. Patients with mild SCA did prefer follow-up in an expert center, which may be due to their better physical possibilities, as compared to patients with more severe SCA. Translating this into clinical practice, future care pathways might be organized in a way that patients, especially those in more advanced disease stages, can receive follow-up to further monitor the effect of new invasive genetic treatments in a local hospital.\u003c/p\u003e \u003c/div\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis study shows that the frequency and mode of administration, and the chance of a beneficial effect are both of influence on the decision for a certain genetic intervention in patients with SCA and HD. Patients prefer repeated lumbar punctures ( 6 times or 12 times yearly) less compared to a single operation. The scientific versus patient perspective on the ideal timing of genetic interventions requires further study. These results provide guidance to design upcoming clinical trials and, if proven effective, future implementation of genetic interventions in care pathways.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthical approval and consent to participate\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the\u0026nbsp;Regional Committee on Research involving Human Subjects Arnhem-Nijmegen\u0026nbsp;(file number: 2021-9700). Written informed consent was given by all participants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAvailability of data and materials\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset generated during this study are not publicly available due to privacy restrictions. Summaries are available upon reasonable request from the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBart van de Warrenburg receives research support from NOW, ZonMw, Hersenstichting, Radboud university medical center, the Brugling Fonds, and Gossweiler Foundation. The authors have stated explicitly that there are no conflicts of interest in connection with this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by the Academisch Alliantie Fonds (Radboudumc and Maastricht UMC+, the Netherlands). The funding source had no role in the preparation of data or the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthor\u0026rsquo;s Contributions\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNvO: conceptualization, data collection, data analysis, writing \u0026ndash; original draft, writing review \u0026amp; editing.\u003cbr\u003e\u0026nbsp;MO: conceptualization, writing review \u0026amp; editing, supervision.\u003cbr\u003e\u0026nbsp;JG: conceptualization, writing review \u0026amp; editing, supervision.\u003cbr\u003e\u0026nbsp;BE: conceptualization, data analysis, writing review \u0026amp; editing, supervision.\u003cbr\u003e\u0026nbsp;BvdW: conceptualization, writing review \u0026amp; editing, supervision.\u003cbr\u003e\u0026nbsp;All authors read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgement\u003cbr\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eWe thank Teije van Prooije for his help with recruiting the participants with SCA1 for the interviews.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eA novel gene containing a trinucleotide repeat that is expanded and unstable on Huntington\u0026apos;s disease chromosomes. 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Mov Disord. 1996;11(2):136-42.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"orphanet-journal-of-rare-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ojrd","sideBox":"Learn more about [Orphanet Journal of Rare Diseases](http://ojrd.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ojrd/default.aspx","title":"Orphanet Journal of Rare Diseases","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-3576801/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3576801/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAlthough genetic interventions are on the horizon for some polyglutamine expansion diseases, such as subtypes of spinocerebellar ataxia (SCA) and Huntington\u0026rsquo;s disease (HD), the patients\u0026rsquo; preferences regarding these new therapies are unclear. This study aims to what extent different characteristics of genetic interventions affect the preferences of patients with SCA and HD with regard to these interventions.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eManifest and premanifest patients with SCA or HD were recruited online by platforms of patient associations. The respondents conducted a questionnaire that included a discrete choice experiment (DCE). The experimental design included 24 choice sets, but these were divided into three blocks of eight to reduce the number of tasks per respondent. Each choice set included two alternative treatments and consisted of four attributes (mode and frequency of administration, chance of a beneficial effect, risks, and follow-up), each with three or four different levels. The forced choice-elicitation format was used. Data were analyzed by using a multinominal logistic regression model.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eResponses of 216 participants were collected. The mode and frequency of administration of a genetic intervention, as well as the chance of a beneficial effect both influence the choice for a genetic intervention. Respondents less prefer repeated lumbar punctures compared to a single operation. As expected, a higher beneficial effect of treatment was preferred. Risks and follow-up did not influence the choice for a genetic intervention. Completing the DCE appeared difficult for some respondents, in particular for patients in a more severe disease stage of HD.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe results can be used for the design and implementation of future genetic interventional trials and care pathways for patients with rare movement disorders such as SCA and HD.\u003c/p\u003e","manuscriptTitle":"Preferences for genetic interventions for SCA and Huntington’s disease: results of a discrete choice experiment among patients.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-10 15:58:15","doi":"10.21203/rs.3.rs-3576801/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Minor revision","date":"2024-02-12T22:31:24+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2024-01-08T17:47:26+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-01-08T08:50:47+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-11-10T13:11:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"Orphanet Journal of Rare Diseases","date":"2023-11-08T13:49:12+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"orphanet-journal-of-rare-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ojrd","sideBox":"Learn more about [Orphanet Journal of Rare Diseases](http://ojrd.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ojrd/default.aspx","title":"Orphanet Journal of Rare Diseases","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c42e9d94-1eec-4ebe-99e9-2869f99df3d3","owner":[],"postedDate":"January 10th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-11-04T16:24:46+00:00","versionOfRecord":{"articleIdentity":"rs-3576801","link":"https://doi.org/10.1186/s13023-024-03408-2","journal":{"identity":"orphanet-journal-of-rare-diseases","isVorOnly":false,"title":"Orphanet Journal of Rare Diseases"},"publishedOn":"2024-10-28 15:57:25","publishedOnDateReadable":"October 28th, 2024"},"versionCreatedAt":"2024-01-10 15:58:15","video":"","vorDoi":"10.1186/s13023-024-03408-2","vorDoiUrl":"https://doi.org/10.1186/s13023-024-03408-2","workflowStages":[]},"version":"v1","identity":"rs-3576801","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3576801","identity":"rs-3576801","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}