Usefulness of EQ-5D in Assessing Health Status in Primary Care Patients with Major Depressive Disorder

Major depressive disorder (MDD) is common in primary care patients [1] with a lifetime prevalence rate in the French population of 10–25% in women and 5–12% in men [2]. Depression is associated with marked decreases in functioning, well being and health-related quality of life (HRQL) [3, 4], and an increases in disability days [5], use of health services and overall societal costs [6]. Antidepressant treatments are effective in reducing depression severity [7, 8] and in increasing patient functioning and HRQL [9, 10].

The Washington Panel on Cost-Effectiveness in Health and Medicine recommended the use of HRQL in the evaluation of health care interventions [11]. For this purpose, HRQL measurement needs to express patient health status on a scale where perfect health and death are valued 1 and 0 respectively. When such quality of life data are combined with corresponding data on the quantity of life, then the consequences of treatment are measured in units of Quality-Adjusted Life Years (QALYs) [12]. Where QALYs are calculated for social decision making purposes then the HRQL measures used to make the quality adjustment should be based on the preferences of the population as a whole. Such social preferences are only available for a limited number of HRQL measures and for a limited number of countries. EQ-5D is one such measure that has been calibrated in this way.

Studies of physical illnesses have suggested that patient's values for their own health state affect decisions concerning treatment and its outcomes [13‐15]. Several studies focused on establishing utility scores for a variety of health states in various mental illnesses, including schizophrenia [16], depression in primary care [17], temporary states of depression [18, 19] and treatment-related side effects [20, 21]. Health states in depression have been characterised by the presence or absence of symptoms, and depressed patients are usually categorised as responders and remitters using classical rating scales [22]. As responders sometimes present residual depressive symptoms, we classify patients as "Responder remitters", "Responders non-remitter" and "Non-responders".

The objectives of this paper are to describe the impact on HRQL of patients with MDD treated in a primary care setting, and to examine variations in terms of patients' demographic and clinical characteristics.

This study evaluated the usefulness of EQ-5D in assessing health status of primary care patients with major depressive disorder.

The sampling of our study is representative of the primary care depressed population in France [2]. 8% of the patients rated their health state as worse than death. This result is not surprising given the relationship between depression and suicide [31, 32]. Despite different approaches to measuring health state utilities using standard gamble, time trade-off or rating scales, the findings of our study agree with those previously reported: the baseline mean utility of an untreated depression was 0.33, compared to 0.30 for Revicki [21] and 0.32 for Bennett [33]. Patient-rated EQ-5D_ST scores after the eight-week follow-up period was 0.78, which is comparable to utilities reported in other studies (0.79 [33]; 0.74 [21]; 0.76 [34]; 0.70 [35]). The main interest is that EQ-5D_ST values are easy to collect in large sample surveys due to the brevity of EQ-5D classification system with its 5 dimensions and 3 levels.

No differences in EQ-5D_ST utilities were observed by demographic characteristics, which is comparable to previous results in depressed patients [21, 34, 35]. More severely depressed patients reported utilities that were 0.30 points lower than less severely depressed patients at baseline. Several researchers have suggested that differences in utility greater than 0.05 are clinically important [12, 36]. These findings may reflect clinically important differences.

As demonstrated in previous studies [21, 37], we found that the EQ-5D_ST score and other HRQL measures shared only about 40% of variance. Utilities measure a patient's preference for their health state, while HRQL scales assess the patient's report of their functioning and well-being. Although these two concepts are related they are not identical [38], and measuring both may lead to a better understanding of reasons for non-compliance to treatment regimens.

There are several limitations that need to be considered when interpreting the results of this study. First, the study does not take into account the antidepressant prescribed or their side effects, which may influence patients' ratings [21, 39]. Second, the concomitant impact of depression and chronic medical conditions could not be examined in this sample. It is likely that the health state utilities of patients with depression, in addition to a chronic medical disease would be significantly reduced [17]. Lastly, a limitation of the analysis presented in this study relates to the source of the utility weights used to compute the EQ-5D_ST. Given that this was a national study conducted in France it may have been better to use social preference values based on the French population. Unfortunately, at the time of writing these values were not available for EQ-5D_ST. Weights were therefore adopted from a major UK study that provided the most robust technical estimates widely used in the evaluation of EQ-5D_ST in countries that lack their own national reference data.

Utility scores are needed for calculating QALYs, which are used as indicators of effectiveness or outcome in economic evaluations [35, 36, 40]. It is debatable whether or not patient or general population utilities should be used in cost-effectiveness studies [40]. Nevertheless, patients with experience in the disease may be the best providers of health state preference data. Cost-effectiveness studies are required to help clinicians and health care decision-makers in determining the impact of new antidepressants on both patient outcomes and medical or overall societal costs. Understanding patient preferences for depression outcomes is important for economic evaluations of new antidepressants, as well as for understanding patient behaviour and compliance to antidepressant regimens. Such a measure can be applied to cost-utility analyses either within clinical decision modelling studies or within prospective, randomised clinical trials and offers additional scope for the analysis and reporting of data derived from clinical trials of new compounds.