Matching-Adjusted Indirect Comparison of the Long-Term Efficacy Maintenance and Adverse Event Rates of Lebrikizumab versus Dupilumab in Moderate-to-Severe Atopic Dermatitis.

INTRODUCTION: Lebrikizumab and dupilumab are monoclonal antibodies approved for treating moderate-to-severe atopic dermatitis (AD). Both have demonstrated efficacy and safety over the 16-week SOLOs and ADvocate trials. However, AD is a chronic and relapsing inflammatory disease, and the long-term maintenance of efficacy is critical for achieving disease control from the perspective of patients, physicians, and regulatory agencies. This study aims to compare the long-term efficacy and safety of lebrikizumab every 4 weeks (Q4W) and dupilumab every week or every 2 weeks (QW/Q2W) among adult patients who have achieved treatment efficacy following the induction period of 16 weeks. METHODS: Lebrikizumab's efficacy was assessed using individual patient data (IPD) from the ADvocate 1 and 2 monotherapy trials. Dupilumab's efficacy was evaluated using aggregate data from the adult-exclusive SOLO-CONTINUE trial. Due to the absence of a common comparator trial arm, we employed an unanchored matching-adjusted indirect comparison (MAIC), a robust methodology widely accepted by health technology assessment (HTA) agencies. This re-weights ADvocate IPD to align with SOLO-CONTINUE's prognostic factors and effect modifiers. We compared lebrikizumab's adjusted outcomes with dupilumab outcomes at week 52, focusing on 75% improvement in the Eczema Area and Severity Index from baseline (EASI-75), Investigator's Global Assessment (IGA) score of 0 or 1, and overall adverse event (AE) rates. Sensitivity analyses were conducted to test various combinations of matching variables. RESULTS: Adults on lebrikizumab Q4W were more likely to maintain IGA 0/1 through the 36-week maintenance period (weeks 16-52) compared with those on dupilumab QW/Q2W [risk ratio (RR) 1.334; 95% confidence interval (CI) 1.02-1.74; p = 0.035]. Both treatments demonstrated comparable efficacy in terms of EASI-75 maintenance (RR 0.937; 95% CI 0.78-1.13; p = 0.490) and similar AE rates (RR 1.052; 95% CI 0.90-1.23; p = 0.526). Sensitivity analyses substantiated these findings. CONCLUSIONS: Our findings suggest that lebrikizumab Q4W may provide equal or superior long-term maintenance of efficacy measured with EASI-75 and IGA 0/1 compared with dupilumab QW/Q2W, with the advantage of requiring less frequent doses.

Beyond 10-year lead-times in EQ-5D-5L: leveraging alternative lead-times in willingness-to-accept questions to capture preferences for worse-than-dead states and their implication.

BACKGROUND: A fixed 10-year lead-time in composite time-trade-off (C-TTO) tasks might compromise the precision of utility values below - 1. This study explored how alternative lead-times (ALTs) influence EQ-5D-5L value sets and their implications in economic evaluations. METHODS: Leveraging data from Taiwan's EQ-5D-5L valuation and capitalizing on its exploratory willingness-to-accept question, we explored participants' quantification of "worse-than-dead (WTD)" health states with ALTs up to 50 years. We then derived alternative value sets incorporating these ALTs through interval regression and compared them against those from conventional models. To evaluate their impact on health change valuation, we simulated utility differences for all possible EQ-5D-5L health-state-pairs using each value set. RESULTS: With a salient floor effect observed in the C-TTO values, the model with ALT led to a wider range of predicted utilities ( - 2.3897 ~ 1), compared with those of conventional models (generalized least squares (GLS): - 0.7773 ~ 1; Tobit-GLS: - 0.9583 ~ 1). Compared to the Tobit-GLS model, the model with ALT increased the numerical distance in 80% of health-state-pairs, with 11% decreasing and 9% altering direction (e.g., positive to negative) in utility differences. CONCLUSIONS: While ALTs offer insights into patient preferences, their integration into economic evaluations might require rescaling. Future research should prioritize advanced rescaling methods or enhanced elicitation strategies for populations with substantial censoring. This is pivotal for improving the elicitation of extreme WTD states and accurately discerning the relative distances between health states. Countries developing EQ-5D-5L value sets should consider pilot studies and incorporating region-specific questions on social determinants, especially where pronounced floor effects are suspected.

Health-Related Quality of Life and Perceived Burden of Informal Caregivers of Patients with Rare Diseases in Selected European Countries.

Most of rare disease (RD) patients are assisted in their homes by their family as informal caregivers, causing a substantial burden among family members devoted to care. The role of informal caregivers has been associated with increased levels of stress, poor physical/mental health and impaired HRQOL. The present study assessed the impact on HRQOL and perceived burden of long-term informal caregiving, as well as the inter-relationships of individuals affected by different RD in six European countries, taking advantage of the data provided by the BURQOL-RD project (France, Germany, Italy, Spain, Sweden and UK). Correlation analysis was used to explore the relation between caregiver HRQOL and caregiver burden (Zarit Burden Interview). Multinomial logistic regression models were used to explore the role of explanatory variables on each domain of caregivers HRQOL measured by EQ-5D. Caregivers' HRQOL is inversely correlated with burden of caring. Mobility dimension of EQ-5D was significantly associated with patients age, time devoted to care by secondary caregivers, patient gender and patient utility index. Patients' age, burden scores and patient utility index significantly predict the capacity of caregivers to perform activities of daily living. Employed caregivers are less likely of reporting 'slight problems' in pain/discomfort dimensions than unemployed caregivers. The EQ-5D instrument is sensitive to measure differences in HRQOL between caregivers with different levels of burden of care.

Valuing EQ-5D-Y-3L Health States Using a Discrete Choice Experiment: Do Adult and Adolescent Preferences Differ?

BACKGROUND: An important question in the valuation of children's health is whether the preferences of younger individuals should be captured within value sets for measures that are aimed at them. This depends on whether younger individuals can complete valuation exercises and whether their preferences differ from those of adults. This study compared the preferences of adults and adolescents for EQ-5D-Y-3L health states using latent scale values elicited from a discrete choice experiment (DCE). METHODS: An online DCE survey, comprising 15 pairwise choices, was provided to samples of UK adults and adolescents (aged 11-17 y). Adults considered the health of a 10-year-old child, whereas adolescents considered their own health. Mixed logit models were estimated, and comparisons were made using relative attribute importance (RAI) scores and a pooled model. RESULTS: In total, 1000 adults and 1005 adolescents completed the survey. For both samples, level 3 in pain/discomfort was most important, and level 2 in self-care the least important, based on the relative magnitudes of coefficients. The RAI scores (normalized on self-care) indicated that adolescents gave less weight relative to adults to usual activities (1.18 v. 1.51; P < 0.05), pain/discomfort (1.77 v. 3.12; P < 0.01), and anxiety/depression (1.64 vs. 2.65; P < 0.01). The pooled model indicated evidence of differences between the two samples in both levels in pain/discomfort and anxiety/depression. LIMITATIONS: The perspective of the DCE task differed between the 2 samples, and no data were collected to anchor the DCE data to generate value sets. CONCLUSIONS: Adolescents could complete the DCE, and their preferences differed from those of adults taking a child perspective. It is important to consider whether their preferences should be incorporated into value sets.

[Cost-effectiveness methods of newborn screening assessment.] / Métodos para la evaluación económica de programas de cribado neonatal.

Newborn screening programs are a fundamental tool for secondary prevention or pre-symptomatic detection of certain conditions. The implementation of a newborn screening program requires an evaluation of effectiveness, safety, cost-effectiveness, feasibility and budget impact. Economic evaluation aims to contribute to the sustainability and solvency of health systems, especially when it comes to informing about financing health interventions with public funds. This funding must be justified on the basis of robust evidence of effectiveness, safety, cost-effectiveness, and acceptability. One of the most important limitations when evaluating the cost-effectiveness of a newborn screening program for hereditary disorders or congenital errors of metabolism is the scarcity of scientific evidence that limits the robustness of the economic analysis. Given the low availability of data, the use of expert opinion as a data source is unavoidable to complete the information. However, two main problems make it difficult to synthesize data obtained from various sources: biases and heterogeneity. Moreover, the measurement of quality-adjusted life years (QALYs) in pediatric populations poses serious methodological challenges. In Spain, although there is some heterogeneity in the supply of newborn screening programs between regions, guidelines are being established based on the best available scientific evidence to achieve the homogenization of newborn screening policies and programs at national level.

Los programas de cribado neonatal son una herramienta fundamental para la prevención secundaria o detección presintomática de determinadas afecciones. La implantación de un programa de cribado neonatal requiere necesariamente de una evaluación de su efectividad, seguridad, coste-efectividad, factibilidad e impacto presupuestario. La evaluación económica pretende contribuir a la sostenibilidad y solvencia de los sistemas sanitarios, especialmente a la hora de informar sobre la posible financiación, con fondos públicos, de intervenciones sanitarias como el cribado poblacional. Esta financiación debe justificarse en base a pruebas robustas de efectividad, seguridad, coste-efectividad y aceptabilidad. Una de las limitaciones más importantes a la hora de evaluar el coste-efectividad de un programa de cribado neonatal de trastornos hereditarios o de errores congénitos del metabolismo es la escasez de evidencia científica que limita la solidez y robustez del análisis de evaluación económica. Dada la baja disponibilidad de datos, el uso de la opinión de expertos como fuente de datos es inevitable para completar la información necesaria. Sin embargo, dos problemas principales dificultan la síntesis de datos obtenidos de varias fuentes: sesgos y heterogeneidad. Por otro lado, la medición de los años de vida ajustados por calidad (AVAC) en poblaciones pediátricas plantea serios desafíos metodológicos en un análisis de evaluación económica. En España, aunque existe cierta heterogeneidad en la oferta de programas de cribado neonatal entre CC.AA., se están estableciendo directrices basadas en la mejor evidencia científica disponible para conseguir la homogeneización de políticas y programas de cribado neonatal a nivel nacional.

An exploration of methods for obtaining 0 = dead anchors for latent scale EQ-5D-Y values.

OBJECTIVES: Discrete choice experiments (DCEs) can be used to obtain latent scale values for the EQ-5D-Y, but these require anchoring at 0 = dead to meet the conventions of quality-adjusted life year (QALY) estimation. The primary aim of this study is to compare four preference elicitation methods for obtaining anchors for latent scale EQ-5D-Y values. METHODS: Four methods were tested: visual analogue scale (VAS), DCE (with a duration attribute), lag-time time trade-off (TTO) and the location-of-dead (LOD) approach. In computer-assisted personal interviews, UK general public respondents valued EQ-5D-3L health states from an adult perspective and EQ-5D-Y health states from a 10-year-old child perspective. Respondents completed valuation tasks using all four methods, under both perspectives. RESULTS: 349 interviews were conducted. Overall, respondents gave lower values under the adult perspective compared to the child perspective, with some variation across methods. The mean TTO value for the worst health state (33333) was about equal to dead in the child perspective and worse than dead in the adult perspective. The mean VAS rescaled value for 33333 was also higher in the child perspective. The DCE produced positive child perspective values and negative adult perspective values, though the models were not consistent. The LOD median rescaled value for 33333 was negative under both perspectives and higher in the child perspective. DISCUSSION: There was broad agreement across methods. Potential criteria for selecting a preferred anchoring method are presented. We conclude by discussing the decision-making circumstances under which utilities and QALY estimates for children and adults need to be commensurate to achieve allocative efficiency.

Do people with private health insurance attach a higher value to health than those without insurance? Results from an EQ-5D-5 L valuation study in Ireland.

BACKGROUND: Differences in healthcare use could relate to differences in the values assigned health as well as to differences in access. We sought to establish whether there existed evidence of differences in values assigned health states between individuals with and without insurance in Ireland. METHODS: Using the EuroQol Valuation Technology (EQ-VT), EQ-5D-5 L valuation tasks were administered to a sample of 1160 residents of Ireland in 2015/16. Censored panel regression analyses were used to estimate the values assigned health states. Private insurance was entered among a range of covariates to explain health preferences as a binary variable. A range of confirmatory analyses were undertaken. RESULTS: In the primary analysis, possession of private health insurance was not a significant determinant of health preferences. Across a range of confirmatory analyses limited evidence of any difference in values related to health insurance emerged. CONCLUSIONS: Insurance status has been shown to be a significant determinant of healthcare utilization in Ireland after need has been controlled for. Our analysis provides no compelling evidence that meaningful differences exist in the values accorded health between those with and without health insurance.

Application of two-part models and Cholesky decomposition to incorporate covariate-adjusted utilities in probabilistic cost-effectiveness models / Aplicación de los modelos en dos etapas y la descomposición de Cholesky para incorporar las utilidades ajustadas en los modelos probabilísticos de coste-efectividad

This study aimed to explain a joint statistical procedure (two-part models and Cholesky decomposition) to incorporate second-order uncertainty from covariate adjusted mean utility functions in probabilistic cost-effectiveness models. First, two-part models were applied to obtain parameters for the utility function. Second, a new set of correlated parameters for each simulation was obtained by Cholesky decomposition. The procedure was applied to EuroQol5D-5L in the Spanish Health Survey (21,007 adults). An example for the first simulation showed that 71% of men aged 60 years, high social status and normal weight were in perfect health, and in those not in perfect health, the expected utility was 0.8474 (= 1 − 0.1526). Therefore, their estimated mean utility value was 0.9559. Mean utility values in the interval (− ∞1] were calculated and their associated uncertainty incorporated in the cost-effectiveness models, based on the uncertainty related to correlated parameters in the utilities function

El objetivo de este estudio fue explicar el procedimiento estadístico conjunto (modelos en dos etapas y descomposición de Cholesky) para incorporar la incertidumbre de segundo orden asociada a la función de utilidad media ajustada por variables en los modelos probabilísticos de coste-efectividad. Primero se aplicaron los modelos en dos etapas para obtener los parámetros de la función de utilidad. Segundo, para cada simulación, se obtuvo un nuevo conjunto de parámetros correlacionados utilizando la descomposición de Cholesky. El procedimiento se aplicó al cuestionario EuroQol5D-5L de la Encuesta Nacional de Salud en España (21.007 adultos). El ejemplo de una primera simulación mostró que el 71% de los hombres de 60 años, con clase social alta y peso normal tenían una salud perfecta, y en aquellos que no tenían una salud perfecta la utilidad esperada fue de 0,8474 (= 1 − 0,1526). Por lo tanto, su utilidad media estimada fue de 0,9559. Se calcularon utilidades medias con valores comprendidos en el intervalo (-∞1] y se incorporó la incertidumbre asociada a ellos en los modelos de coste-efectividad, basándose en la incertidumbre correspondiente a los parámetros correlacionados de la función de utilidad

Application of two-part models and Cholesky decomposition to incorporate covariate-adjusted utilities in probabilistic cost-effectiveness models.

This study aimed to explain a joint statistical procedure (two-part models and Cholesky decomposition) to incorporate second-order uncertainty from covariate adjusted mean utility functions in probabilistic cost-effectiveness models. First, two-part models were applied to obtain parameters for the utility function. Second, a new set of correlated parameters for each simulation was obtained by Cholesky decomposition. The procedure was applied to EuroQol5D-5L in the Spanish Health Survey (21,007 adults). An example for the first simulation showed that 71% of men aged 60 years, high social status and normal weight were in perfect health, and in those not in perfect health, the expected utility was 0.8474 (= 1 - 0.1526). Therefore, their estimated mean utility value was 0.9559. Mean utility values in the interval (- ∞1] were calculated and their associated uncertainty incorporated in the cost-effectiveness models, based on the uncertainty related to correlated parameters in the utilities function.

Using a stated preference discrete choice experiment to assess societal value from the perspective of patients with rare diseases in Italy.

BACKGROUND: Decision makers have huge problems when attempting to attribute social value to the improvements achieved by new drugs, especially when considering the use of orphan drugs for rare diseases. We present the results of a pilot study aimed to investigate patient preferences regarding public funding for drugs used to treat rare diseases. METHODS: An online questionnaire was used as a discrete choice experiment (DCE) survey to explore the preferences of patients with cystic fibrosis and haemophilia in Italy. The questionnaire focused on relevant issues that were defined in a review of the literature. A conditional logistic model showed preferences for specific attributes. RESULTS: A total of 54 questionnaires (20% response rate) were completed. The issues that received the greatest attention were improvement in health, treatment cost and value for money. However, disease severity and the availability of other treatments were important social values that could not be ignored. CONCLUSIONS: The findings presented here provide evidence as to what patients with cystic fibrosis or haemophilia think are the most important considerations on which to base decisions in health technology scenarios, and regarding the priorities for funding.

Overview, Update, and Lessons Learned From the International EQ-5D-5L Valuation Work: Version 2 of the EQ-5D-5L Valuation Protocol.

A standardized 5-level EuroQol 5-dimensional questionnaire (EQ-5D-5L) valuation protocol was first used in national studies in the period 2012 to 2013. A set of problems encountered in this initial wave of valuation studies led to the subsequent refinement of the valuation protocol. To clarify lessons learned and how the protocol was updated when moving from version 1.0 to the current version 2.1 and 2.0, this article will (1) present the challenges faced in EQ-5D-5L valuation since 2012 and how these were resolved and (2) describe in depth a set of new challenges that have become central in currently ongoing research on how EQ-5D-5L health states should be valued and modeled.

The EQ-5D-5L Valuation study in Thailand.

BACKGROUND: At present, health technology assessment (HTA) guidelines of many countries including Thailand have recommended EQ-5D as the preferred method for assessing utility. This study aims to generate an EQ-5D-5L value set based on societal preferences of Thai population. METHODS: A 1,207 representative sample was recruited using a stratified multi-stage quota sampling technique. Face-to-face, computer-assisted interviews using the EuroQol Valuation Technology (EQ-VT) software were employed. To elicit preference score, each respondent was asked to value health states using composite time trade-off (cTTO), and discrete choice experiment (DCE). All data were integrated and analyzed using a hybrid regression model to estimate the value set. RESULTS: Characteristics of 1,207 participants were generally similar to those of Thai general population. The coefficients generated from a hybrid model were logically consistent. The second best value is 0.9436 for health state 11121 and the worst state (55555) value is -0.4212. Mobility shows the greatest impact to utility decrement. CONCLUSIONS: Our study developed a Thai value set for EQ-5D using hybrid model. The findings from this study are of important to facilitate health technology assessment studies to inform policy decision-making as well as to promote the use of EQ-5D-5L in various health research in Thailand.

Assessing the Use of a Feedback Module to Model EQ-5D-5L Health States Values in Hong Kong.

BACKGROUND: An international valuation protocol exists for obtaining societal values for each of the 3125 health states of the five-level EuroQol-five dimensions (EQ-5D-5L) questionnaire. A feedback module (FM) that can be related to theoretical models used in behavioral economics was recently included in this protocol. OBJECTIVES: Our objective was to assess the impact of using an FM to estimate an EQ-5D-5L value set in Hong Kong. METHODS: EQ-5D-5L health states were elicited using a composite time trade-off (C-TTO) and a discrete-choice (DC) experiment. Use of the FM according to participant characteristics and the impact of the FM on the number of inconsistent C-TTO responses were assessed. We employed a main-effects hybrid model that combined data from both elicitation techniques. RESULTS: In total, 1014 individuals completed the survey. The sample was representative of the general Chinese Hong Kong population in terms of sex, educational attainment, marital status, and most age groups but not for employment status. The use of the FM reduced the number of C-TTO inconsistencies. Participant characteristics differed significantly between those who used and did not use the FM. The model without a constant resulted in logical consistent coefficients and was therefore selected as the model to produce the value set. The predicted EQ-5D-5L values ranged from -0.864 to 1. CONCLUSIONS: The use of an FM to allow participants to exclude C-TTO responses reduced the number of inconsistent responses and improved the quality of the data when estimating an EQ-5D-5L value set in Hong Kong.

The Indonesian EQ-5D-5L Value Set.

BACKGROUND: The EQ-5D is one of the most used generic health-related quality-of-life (HRQOL) instruments worldwide. To make the EQ-5D suitable for use in economic evaluations, a societal-based value set is needed. Indonesia does not have such a value set. OBJECTIVE: The aim of this study was to derive an EQ-5D-5L value set from the Indonesian general population. METHODS: A representative sample aged 17 years and over was recruited from the Indonesian general population. A multi-stage stratified quota method with respect to residence, gender, age, level of education, religion and ethnicity was utilized. Two elicitation techniques, the composite time trade-off (C-TTO) and discrete choice experiments (DCE) were applied. Interviews were undertaken by trained interviewers using computer-assisted face-to-face interviews with the EuroQol Valuation Technology (EQ-VT) platform. To estimate the value set, a hybrid regression model combining C-TTO and DCE data was used. RESULTS: A total of 1054 respondents who completed the interview formed the sample for the analysis. Their characteristics were similar to those of the Indonesian population. Most self-reported health problems were observed in the pain/discomfort dimension (39.66%) and least in the self-care dimension (1.89%). In the value set, the maximum value was 1.000 for full health (health state '11111') followed by the health state '11112' with value 0.921. The minimum value was -0.865 for the worst state ('55555'). Preference values were most affected by mobility and least by pain/discomfort. CONCLUSIONS: We now have a representative EQ-5D-5L value set for Indonesia. We expect our results will promote and facilitate health economic evaluations and HRQOL research in Indonesia.

Less Is More: Cross-Validation Testing of Simplified Nonlinear Regression Model Specifications for EQ-5D-5L Health State Values.

BACKGROUND: The conventional method for modeling of the five-level EuroQol five-dimensional questionnaire (EQ-5D-5L) health state values in national valuation studies is an additive 20-parameter main-effects regression model. Statistical models with many parameters are at increased risk of overfitting-fitting to noise and measurement error, rather than the underlying relationship. OBJECTIVES: To compare the 20-parameter main-effects model to simplified, nonlinear, multiplicative regression models in terms of how accurately they predict mean values of out-of-sample health states. METHODS: We used data from the Spanish, Singaporean, and Chinese EQ-5D-5L valuation studies. Four models were compared: an 8-parameter model with single parameter per dimension, multiplied by cross-dimensional parameters for levels 2, 3, and 4; 9- and 11-parameter extensions with handling of differences in the wording of level 5; and the "standard" additive 20-parameter model. Fixed- and random-intercept variants of all models were tested using two cross-validation methods: leave-one-out at the level of valued health states, and of health state blocks used in EQ-5D-5L valuation studies. Mean absolute error, Lin concordance correlation coefficient, and Pearson R between observed health state means and out-of-sample predictions were compared. RESULTS: Predictive accuracy was generally best using random intercepts. The 8-, 9-, and 11-parameter models outperformed the 20-parameter model in predicting out-of-sample health states. CONCLUSIONS: Simplified nonlinear regression models look promising and should be investigated further using other EQ-5D-5L data sets. To reduce the risk of overfitting, cross-validation is recommended to inform model selection in future EQ-5D valuation studies.

Transforming Latent Utilities to Health Utilities: East Does Not Meet West.

Discrete choice experiments (DCEs) are a promising alternative to more resource-intensive preference elicitation methods such as time trade-off (TTO), as pairwise comparisons are more amenable to online completion, which can save time and money. However, modeling DCE data produces latent utilities which are on an unknown scale. Therefore, latent utilities need to be transformed to a full health-dead scale before they can be used in quality-adjusted life year calculations. We aimed to explore transformation functions from DCE-derived latent utilities to TTO-derived health utilities. We used EQ-5D-5L valuation data from eight different countries that collected both DCE and TTO data by using a standardized protocol. Results found less variation in the function that transformed latent utilities to health utilities in the western countries than in the eastern countries. While a global transformation function is not recommended, results suggest that regional transformation functions could potentially be used to derive health utilities from DCE data. Copyright © 2016 John Wiley & Sons, Ltd.

An EQ-5D-5L value set based on Uruguayan population preferences.

PURPOSE: To derive a value set from Uruguayan general population using the EQ-5D-5L questionnaire and report population norms. METHODS: General population individuals were randomly assigned to value 10 health states using composite time trade off and 7 pairs of health states through discrete choice experiments. A stratified sampling with quotas by location, gender, age and socio-economic status was used to respect the Uruguayan population structure. Trained interviewers conducted face-to-face interviews. The EuroQol valuation technology was used to administer the protocol as well as to collect the data. OLS and maximum likelihood robust regression models with or without interactions were tested. RESULTS: We included 794 respondents between 20 and 83 years. Their characteristics were broadly similar to the Uruguayan population. The main effects robust model was chosen to derive social values. Values ranged from -0.264 to 1. States with a misery index = 6 had a mean predicted value of 0.965. When comparing the Uruguayan population with the Argentinian EQ-5D-5L crosswalk value set, the prediction for states which differed from full health only in having one of the dimensions at level 2 were about 0.05 higher in Uruguay. The mean index value, using the selected Uruguayan EQ-5D-5L value set, for the general population in Uruguay was 0.895. In general, older people had worse values and males had slightly better values than females. CONCLUSION: We derived the EQ-5D-5L Uruguayan value set, the first in Latin America. These results will help inform decision-making using economic evaluations for resource allocation decisions.