Validity of the EQ-5D as a generic health outcome instrument in a heroin-dependent population
Introduction
Nowadays, many proven effective interventions are available for the treatment of heroin-dependent patients (van den Brink and van Ree, 2003). The interventions differ in their target populations, effectiveness and in the costs per treatment. It is common to evaluate new treatments not only in terms of effectiveness or direct health benefit for the patient (clinical outcome), but also in terms of efficiency integrating the costs and changes in health status and comparing it with the best available alternative(s) (Gold et al., 1996). To compare the cost-effectiveness of different interventions and to compare the results with the cost-effectiveness of interventions in other domains of medicine, general and standardized comparable indicators of effect are needed, such as measures assessing health status. One of the most frequently applied general health status measures is the EuroQol questionnaire (EQ-5D, The EuroQol Group, 1990). The EQ-5D is a brief, simple and easy-to-use self-completion questionnaire. It is often used in economic evaluations of health care as a complement to disease-specific outcome measures. The EQ-5D is available in many languages and its use and qualities are described for a growing number of different populations and settings. To our knowledge the EQ-5D, which is an instrument of choice in economic evaluations, has not been used in (randomized) studies in drug-dependent populations, hence, little is known about its validity in these populations (Dijkgraaf et al., 2005).
This paper attempts to establish the validity of the EQ-5D in a population of chronic, treatment-resistant heroin-dependent patients participating in the Dutch heroin trials. The EQ-5D is studied relative to three disease-specific instruments commonly used in addiction research: the Maudsley Addiction Profile (MAP, Marsden et al., 1998), the Symptom Checklist (SCL-90, Arrindell and Ettema, 1986) and the European Addiction Severity Index (EuropASI, Kokkevi and Hartgers, 1995).
Section snippets
Trials, treatments and patients
In two recent Dutch trials, medically co-prescribed heroin in addition to methadone maintenance treatment was compared to methadone maintenance treatment only (n = 549). These trials were conducted among inhaling (n = 375) and injecting (n = 174) heroin-dependent patients and were carried out simultaneously (van den Brink et al., 2003). Participants were chronic heroin-dependent patients who had been treated unsuccessfully in methadone maintenance programs. The trials were multi-centred with
Results
Table 2 shows socio-demographic data and baseline substance abuse characteristics of the study population. Most patients were male, of Dutch/Western-European ethnicity with a mean age of 39 years and of low education. More than two-thirds of all patients lived independently (alone or with partner). About 60% of all patients used heroin predominantly by inhalation. Mean number of years of heroin use on a regular basis was over 16 years.
Summary of the results
The EQ-5D dimensions mobility and self-care generally showed low correlations with the disease-specific items or dimensions from the MAP-HSS, SCL-90 and EuropASI, whereas usual activities showed low to moderate correlations. The pain/discomfort dimension showed low to moderate correlations with all disease-specific measures and a moderate correlation with the MAP-HSS sum score. The anxiety/depression dimension showed moderate to high correlations with the SCL-90 (including the sum score) and
Acknowledgement
This research was funded by the Central Committee on the Treatment of Heroin Addicts (CCBH), Utrecht, The Netherlands.
References (28)
EuroQol: the current state of play
Health Policy
(1996)- et al.
The Addiction Severity Index: reliability and validity in a Dutch addict population
J. Subst. Abuse Treat.
(1989) - et al.
Properties of the 15D and EQ-5D utility measures in a community sample of people with epilepsy
Epilepsy Res.
(2001) - et al.
Pharmacological treatments for heroin and cocaine addiction
Eur. Neuropsychopharmacol.
(2003) - et al.
SCL-90: Handleiding bij een Multidimensionele Psychopathologie Indicator
(1986) - et al.
Convergent and discriminant validation by the multitrait-multimethod matrix
Psychol. Bull.
(1959) - Central Committee on the Treatment of Heroin Addicts (Eds.), 2002. Medical Co-Prescription of Heroin: Two Randomized...
Statistical Power Analysis for the Behavioural Sciences
(1988)- et al.
Development and validation of a multi-dimensional instrument for assessing outcome of treatment among opiate users: the Opiate Treatment Index
Br. J. Addict.
(1992) - et al.
Cost utility analysis of co-prescribed heroin compared with methadone maintenance treatment in heroin addicts in two randomised trials
BMJ
(2005)
Modeling valuations for EuroQol health states
Med. Care
How do scores on the EuroQol relate to scores on the SF-36 after stroke?
Stroke
Cited by (56)
Cannabis use to manage opioid cravings among people who use unregulated opioids during a drug toxicity crisis
2023, International Journal of Drug PolicyHook effect detection and detection-range-controllable one-step immunosensor for inflammation monitoring
2020, Sensors and Actuators, B: ChemicalCitation Excerpt :for Passing–Bablok analysis, and the R Score, slope, and offset values were calculated. The linearity test was carried out in accordance with the CLSI guideline EP06-A [23,24]. The test samples for linearity and the hook effect were spiked to 5, 20, 34, 48, 63, 77, 90, 105, 120, 150, 200, 300, 500, 750, and 1000 mg/L of the cCRP antigen in canine serum.
Opioid agonist treatment reduces losses in quality of life and quality-adjusted life expectancy in heroin users: Evidence from real world data
2019, Drug and Alcohol DependenceCitation Excerpt :Given the higher prevalence rates of chronic medical comorbidities (e.g., HIV or HCV infection) of the OAT group, the non-OAT group showed significantly lower utility values (0.63) along the 8 years of follow-up, and the OAT effect on QOL was even larger after adjustment for confounders. Our findings of QOL corroborate the results of other studies (Larson et al., 2007; Rosenblum et al., 2003; van der Zanden et al., 2006; Volkow and McLellan, 2016). Moreover, we found the difference between the loss-of-LE and loss-of-QALE from improving QOL was 1.9 [ = 9.7-(26.6-18.8)] QALY, which could be directly compared with other clinical conditions, in contrast to estimations using disability-adjusted life year (DALY) (Degenhardt et al., 2013; Peacock et al., 2018).
Integrated cognitive behavioral therapy for ADHD in adult substance use disorder patients: Results of a randomized clinical trial
2019, Drug and Alcohol DependenceCitation Excerpt :Although we originally proposed to use number of days of excessive use in the past two months (Van Emmerik-van Oortmerssen et al, 2013), we later (but before closure of the dataset) decided that a shorter time interval of one week would better reflect substance use at end of treatment as substance use in the past two months reflects substance use during treatment rather than at the end of treatment. Depressive symptoms were assessed with the Beck Depression Inventory (BDI) (Beck and Steer, 1987), anxiety symptoms were assessed with the Beck Anxiety Inventory (BAI) (Beck et al., 1988), and quality of life was assessed with the 3-level EQ-5D (Van der Zanden et al., 2006). These are all self-report instruments.