The responsiveness of EQ-5D utility scores in patients with depression: A comparison with instruments measuring quality of life, psychopathology and social functioning☆
Received 25 January 2007; received in revised form 20 April 2007; accepted 20 April 2007.
Abstract
Introduction
The EQ-5D provides preference weights (utilities) for health-related quality of life to be used for calculating quality-adjusted life years (QALYs) in cost-utility analysis. The aim of this study was to compare differences in EQ-5D utility scores with differences in quality of life, psychopathology, and social functioning scores.
Methods
In an observational longitudinal cohort study, EQ-5D utilities (EQ visual analogue scale (EQ VAS), EQ-5D indices of the United Kingdom (EQ-5D index-UK) and Germany (EQ-5D index-D)) were compared with scores of the WHOQOL-BREF, CGI, and GAF at baseline and at 18 months (N=104). The patients' health status at follow-up was categorized as “worse”, “stable”, or “better” using the EQ-5D transition question (patient-based anchor) and the Bech–Rafaelsen melancholy scale (clinician-based anchor). Effect sizes (ES) were used to compare differences in scores within each group over time; regression analysis was used to derive meaningful difference scores in health status associated with a shift from “stable” to “better” health status.
Results
The most responsive instrument was the CGI (patient-based anchor: ES=|0.98|; clinician-based anchor: ES=|1.35|); responsiveness was large in EQ VAS (patient-based anchor: ES=|0.84|; clinician-based anchor: ES=|1.19|), but rather small to medium for EQ-5D index-UK (patient-based anchor: ES=|0.55|; clinician-based anchor: ES=|0.65|) and EQ-5D index-D (patient-based anchor: ES=|0.41|; clinician-based anchor: ES=|0.45|). Compared with the other instruments, the shift to a “better health status” was smaller if elicited by the EQ-5D indices.
Discussion
Both EQ-5D indices were less responsive and need larger patient samples to detect meaningful differences compared with EQ VAS and the other instruments.
aHealth Economics Research Unit, University of Leipzig, Johannisallee 20, 04317 Leipzig, Germany
bDepartment of Psychiatry, University of Leipzig, Johannisallee 20, 04317 Leipzig, Germany
Corresponding author. University of Leipzig, Health Economics Research Unit, Department of Psychiatry, Johannisallee 20, D-04317 Leipzig, Germany. Tel.: +49 341 97 24560; fax: +49 341 97 24569.
☆ Conflict of interest: All authors declare that they have no conflicts of interest.
Contributors: All authors contributed to and have approved the final manuscript:
Oliver H. Günther undertook the statistical analyze and wrote the first draft and the final version of manuscript. Christiane Roick designed the study and managed the process of data collection. Matthias C. Angermeyer planned the study and reviewed the final manuscript. Hans-Helmut König analyzed the data and reviewed the first draft.
Role of funding source: Funding for this study was provided by German Statutory Health Insurance (grant number 932000-050) and the German Federal Ministry of Education and Research (grant number 01ZZ0106); both had no further role in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication.
ABSTRACT