Differences in utility scores obtained through Brazilian and UK value sets: a cross-sectional study

Abstract

BackgroundMultiple sclerosis (MS) is a chronic disease associated with several impacts; especially regarding patients’ health-related quality of life (HRQL). EuroQol 5 Dimensions questionnaire (EQ-5D) provides self-reported analysis of HRQL and utility scores. Although the British algorithm to convert EQ-5D responses into utility is the most used in the literature, national settings is more appropriate for health policy decision makers. A Brazilian algorithm is available, but not used in MS patients yet. Primarily, this study aimed to address potential differences in utility scores obtained through Brazilian and British value sets. Secondary objective was to determine the role of disability, fatigue and patients socio-demographic and clinical characteristics relevant to MS on the utility scores reported by Brazilian patients.MethodsCross-sectional study with MS patients treated in 8 Brazilian sites. Patients were interviewed about socio-demographic and clinical characteristics, self-reported disability level, HRQL and impact of fatigue on daily living. Disability level, HRQL and impact of fatigue were assessed using the Expanded Disability Status Scale (EDSS) and the Brazilian versions of EQ-5D-3L and Modified Fatigue Impact Scale (MFIS-BR), respectively. Patients were classified in subgroups according to EDSS (mild: 0–3; moderate: 4–6.5; severe: >7) and the self-perceived impact of fatigue (absent: ≤38 points; low: 39–58; high: ≥59). EQ-5D-3 L data was converted into a utility index using an algorithm developed by a Brazilian research group (QALY Brazil) and also the UK algorithm. Differences between utility scores were analysed through Wilcoxon test.ResultsTwo hundred and ten patients were included in the study. Utility index mean scores of 0.59 (SD = 0.22) and 0.56 (SD = 0.32) for the Brazilian and UK algorithms were observed, respectively, without statistically significant difference for the distribution of data (p = 0.586). However, when utility scores were lower than 0.5, Brazilian algorithm provided higher estimates than UK with a better agreement between the scores found closer to 1. The same trend was observed when data was stratified for EDSS and impact of fatigue, with statistically significant difference between scores in categories of mild/severe disabilities and absent/high impact of fatigue.ConclusionsResults suggest that Brazilian value set provided higher utility scores than the UK, particularly for measures below 0.5.