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

Multiple sclerosis (MS) is an inflammatory and demyelinating disease of the central nervous system, which in most cases involves motor, sensory, visual and cognitive alterations, besides other clinical manifestations [1, 2]. It is estimated that about 2.5 million people are living with the disease worldwide. In Brazil, the estimated prevalence ranges from 1.36 to 18.1/100,000 inhabitants, depending on the characteristics of the studied population [1, 3].

The EQ-5D-3L is widely used to measure health-related quality of life in MS. It allows both the descriptive assessment of self-reported impairment in generic dimensions of health and the estimation of utility scores, being one of the most employed instrument in burden of illness studies across several therapeutic areas [4‐17]. Most of the studies using EQ-5D-3L to calculate utility scores in MS patients use the algorithm developed for the United Kingdom (UK), however a national value set is more appropriate for health policy decision makers [18, 19]. Recently, an algorithm to estimate Brazilian preference weights for the 243 health states was described by a Brazilian research group (QALY Brazil), which conducted a household survey using the time trade-off technique to value EQ-5D-3L health states [20].

Thus, the primary aim of this study was to address potential differences in utility scores obtained through Brazilian and British value sets. Additionally, the secondary objective was to determine the role of disability, fatigue and patients socio-demographic and clinical characteristics relevant to MS natural history on the utility scores reported by Brazilian patients.

This study aimed to address potential differences in utilities derived from the well-established UK value set, as described by Dolan et al. [18], and the newly published Brazilian value set, obtained through a household-based study conducted with 9,148 subjects in Minas Gerais state and Rio de Janeiro, Porto Alegre and Recife cities [27]. Patients’ health status was assessed by using EQ-5D-3L and then the EQ-5D-3L data were converted into a utility index using Brazilian and UK value sets. To our knowledge, this is the first study that used the algorithm proposed by QALY Brazil group in a Brazilian sample of patients with MS and also compared the findings with the most used method in literature.

Patients participating in the study were mainly female with a mean age of 40.7 years old. Demographic characteristics are comparable with those previously described for Brazilian MS patients and in studies that assessed quality of life in MS worldwide [4‐16, 28‐31]. Most of the patients had relapsing-remitting MS, moderate disability and a mean utility score of 0.59 (SD = 0.22) and 0.56 (SD = 0.32) for the Brazilian and UK algorithms, respectively. Other studies with similar clinical characteristics described utility scores ranging from 0.491 to 0.698 in MS patients [11, 13, 30].

Considering the total sample, statistical significant differences among the Brazilian (0.59 [SD = 0.22]) and UK (0.56 [SD = 0.32]) algorithms were not observed (p = 0.586, Wilcoxon test for paired samples). This finding is different compared to results from studies comparing value sets for Argentina [32], Chile [32], Denmark [33], Japan [26], United States [26, 33, 34], UK [26, 32‐35] and Spain [35]. However, similar to the results described here, all studies so far have shown lower values when UK algorithm was used for analysis (as compared to the local value set). Statistical tests comparing distribution of data showed that most differences between algorithms can be observed at lower utility scores as shown in this study and also in previous studies comparing local value sets with the one from UK [26, 32‐34].

Differences among utility scores have been attributed in the literature to two main factors: methods used to collect and to rate each of the EQ-5D-3L health status; and cultural characteristics of the sample used [18, 27]. The most important differences among the methods used for UK and the QALY Brazil group were the number of health states used to estimate the value sets and modifications in the data collection process, both proposed by Kind (2009). However, the method to value each of the health states was the same (the time-trade-off technique) [36]. The EQ-5D-3L questionnaire provides 243 possible health states and valuation studies employ a subset of those health states and then apply statistical modelling to derive the remaining states. The Brazilian valuation study used 99 health states while the UK used 42 health states [27, 37]. The use of greater than 42 health states in the rating process was described only by the Brazilian and South Korean studies and researchers have discussed that it may provide the most simple and robust models [38‐47]. The protocol proposed by Kind [36] brings three main updates to the EQ-5D-3L health states valuation process, which consists in shuffling cards describing the states before patients classify each one, the exclusion of the “unconscious” health state and the procedure of giving all cards at the same time to subjects. The rating of value sets is based on the time trade off method, where patients determine how long they could live under the proposed health state and whether it seems similar to death or perfect health. Cultural characteristics may influence the final model of the developed algorithm. To investigate potential cultural factors that may influence the difference in utility scores is not the scope of the present analysis, but previous authors have suggested that this may be explained by country-specific differences in the way people perceive and value health conditions [26, 32, 33, 35].

This study also assessed the role of disability (according to EDSS disability level), fatigue (using MFIS-BR) and patient’s socio-demographic and clinical characteristics relevant to MS natural history on the utility scores reported by Brazilian patients. In terms of self-reported EDSS subgroups (0–3, 4–6.5, 7–9), the increase in self-perceived disability level was accompanied by a decrease in the utility index for both Brazilian and UK value set, which are similar with findings from previous studies [4‐16, 30, 31, 48‐50]. Regarding the assessment of self-reported impact of fatigue, the results observed in our study using the MFIS-BR (59 %) differed from data previously described for Brazil. Nogueira et al. (2009) found higher frequencies of self-reported impact of fatigue (69 %, using the MFIS-BR) and Mendes et al. (2000) using the Fatigue Severity Scale reported a frequency of 67.4 % [51, 52]. Despite this fact, an association between utility and fatigue was also observed, as previously described by other authors who examined the same association using different quality of life measures [52]. Other variables such as age, educational level, employment status, MS type and disease duration were also significantly associated with utility scores. Those between-groups differences were consistent for both Brazilian and UK values.

It is important to consider that this study presented some limitations. Although this was a multicenter study, all study sites were from South and Southeastern Brazilian regions, which are different from other regions in terms of socio-demographic characteristics; and in terms of coverage and access to health care services. Thus, findings may not be representative from the entire country. Another limitation of this study was the self-reported approach to the data collection process, which can lead to memory bias – but is the most adopted approach in patient-reported outcomes studies due to the nature of targeted data. Regarding the variables assessed in this analysis, clinical characteristics (type of MS, recurrence and disease duration) are probably the most prone to bias if self-reported. Thus, the association between those variables and utility scores in MS can be further addressed in studies using other source of data or even combining different ones.

In spite of that, considering the widespread use of EQ-5D-3L in the decision process for evaluating new therapies in health systems worldwide, through cost-utility analysis, these findings could markedly be relevant for policy makers during the health technology assessment of MS treatments that can affect patient’s quality of life by slowing disability worsening and postponing progression to secondary progressive MS, reducing fatigue symptoms, and favoring work productivity [53].

The results suggest that the Brazilian value set provides higher EQ-5D-3L index scores than the UK, particularly for utility scores below 0.5 (the lower the utility, the higher the discrepancy among valuation methods). However, the impact of the differences in these EQ-5D-3L index scores on the outcome of cost-utility analysis needs to be further addressed.