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**Background:** Health state utilities are measures of health-related quality of life that reflect the value placed on improvements in patients’ health status and are necessary for estimation of quality-adjusted life-years. Health state utility data on Fabry disease (FD) are limited. In this study we used vignette (scenario) construction and valuation to develop health state utilities. **Objectives:** The aim of this study was to use vignette construction and valuation to estimate health state utility values suitable for inclusion in economic models of FD treatments. **Methods:** Health state vignettes were developed from semistructured qualitative telephone interviews with patients with FD and informed by published literature and input from an expert. Each vignette was valued in an online survey by members of the United Kingdom (UK) general population using the composite time trade-off (TTO) method, which aims to determine the time the respondent would trade to live in full health compared with each impaired health state. **Results:** Eight adults (50% women) with FD from the UK were interviewed. They were recruited via various approaches, including patient organizations and social media. The interviewees' responses, evidence from published literature, and input from a clinical expert informed the development of 6 health state vignettes (pain, moderate clinically evident FD \[CEFD\], severe CEFD, end-stage renal disease \[ESRD\], stroke, and cardiovascular disease \[CVD\]) and 3 combined health states (severe CEFD + ESRD, severe CEFD + CVD, and severe CEFD + stroke). A vignette valuation survey was administered to 1222 participants from the UK general population who were members of an external surveying organization and agreed to participate in this study; 1175 surveys were successfully completed and included in the analysis. Responses to TTO questions were converted into utility values for each health state. Pain was the highest valued health state (0.465), and severe CEFD + ESRD was the lowest (0.033). **Discussion:** Overall, mean utility values declined as the severity of the vignettes increased, indicating that respondents were more willing to trade life-years to avoid a severe health state. **Conclusions:** Health state vignettes reflect the effects of FD on all major health-related quality-of-life domains and may help to support economic modeling for treatment of FD.

Abstract Background Disease-specific patient-reported outcome measures (PROMs) are fundamental to understanding the impact on, and expectations of, patients with genetic disorders, and can facilitate constructive and educated conversations about treatments and outcomes. However, generic PROMs may fail to capture disease-specific concerns. Here we report the development and validation of a Gaucher disease (GD)-specific PROM for patients with type 1 Gaucher disease (GD1) a lysosomal storage disorder characterized by hepatosplenomegaly, thrombocytopenia, anemia, bruising, bone disease, and fatigue. Results and discussion The questionnaire was initially developed with input from 85 patients or parents of patients with GD1 or GD3 in Israel. Owing to few participating patients with GD3, content validity was assessed for patients with GD1 only. Content validity of the revised questionnaire was assessed in 33 patients in the US, France, and Israel according to US Food and Drug Administration standards, with input from a panel of six GD experts and one patient advocate representative. Concept elicitation interviews explored patient experience of symptoms and treatments, and a cognitive debriefing exercise explored patients’ understanding and relevance of instructions, items, response scales, and recall period. Two versions of the questionnaire were subsequently developed: a 24-item version for routine monitoring in clinical practice (rmGD1-PROM), and a 17-item version for use in clinical trials (ctGD1-PROM). Psychometric validation of the ctGD1-PROM was assessed in 46 adult patients with GD1 and re-administered two weeks later to examine test–retest reliability. Findings from the psychometric validation study revealed excellent internal consistency and strong evidence of convergent validity of the ctGD1-PROM based on correlations with the 36-item Short Form Health Survey. Most items were found to show moderate, good, or excellent test–retest reliability. Conclusions Development of the ctGD1-PROM represents an important step forward for researchers measuring the impact of GD and its respective treatment.

Abstract Background The Quality Adjusted Life Year influences the allocation of significant amounts of healthcare resources. Despite this surprisingly little research effort has been devoted to analysing how beliefs and attitudes to hastening death influence preferences for health states anchored at “dead” and “perfect health”. In this paper we examine how, inter alia, adherence to particular religious beliefs (religiosity) influences attitudes to euthanasia and how, inter alia, attitudes to euthanasia influences the willingness to assign worse than dead (WTD) values to health states using data collected as part of the Irish EQ5D5L valuation study. Methods A sample of 160 respondents each supplied 10 composite time trade-off valuations and information on religiosity and attitudes to euthanasia as part of a larger national survey. Data were analysed using a recursive bivariate probit model in which attitudes to euthanasia and willingness to assign WTD values were analysed jointly as functions of a range of covariates. Results Religiosity was a significant determinant of attitudes to euthanasia and attitudes to euthanasia were a significant determinant of the likelihood of assigning WTD values. A significant negative correlation in errors between the two probit models was observed indicative of support for the hypothesis of endogeneity between attitudes to euthanasia and readiness to assign WTD values. Conclusion In Ireland attitudes and beliefs play an important role in understanding health state preferences. Beyond Ireland this may have implications for: the construction of representative samples; understanding the values accorded health states and; the frequency with which value sets must be updated.