Which health-related quality of life score? A comparison of alternative utility measures in patients with Type 2 diabete
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Which health-related quality of life score? A comparison of alternative utility measures in patients with Type 2 diabetes in the ADVANCE trial Paul Glasziou*1, Jan Alexander2, Elaine Beller2, Philip Clarke3 and the ADVANCE Collaborative Group Address: 1Centre for Evidence-Based Practice, Institute of Health Sciences, Oxford University, Oxford OX3 7LF, UK, 2Queensland Clinical Trials Centre, University of Queensland, Australia and 3School of Public Health, University of Sydney, Australia Email: Paul Glasziou* - [email protected]; Jan Alexander - [email protected]; Elaine Beller - [email protected]; Philip Clarke - [email protected] * Corresponding author
Published: 27 April 2007 Health and Quality of Life Outcomes 2007, 5:21
doi:10.1186/1477-7525-5-21
Received: 28 November 2006 Accepted: 27 April 2007
This article is available from: http://www.hqlo.com/content/5/1/21 © 2007 Glasziou et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract Background: Diabetes has a high burden of illness both in life years lost and in disability through related co-morbidities. Accurate assessment of the non-mortality burden requires appropriate health-related quality of life and summary utility measures of which there are several contenders. The study aimed to measure the impact of diabetes on various health-related quality of life domains, and compare several summary utility measures. Methods: In the ADVANCE (Action in Diabetes and Vascular Disease: Preterax and Diamicron MR Controlled Evaluation) study, 978 Australian patients with Type 2 diabetes completed two health-related quality of life questionnaires at baseline: the EQ-5D and the SF-36v2, from which nine summary utility measures were calculated, and compared. The algorithms were grouped into four classes: (i) based on the EQ-5D; (ii) using fewer items than those in the SF-12 (iii) using the items in the SF-12; and (iv) using all items of the SF-36. Results: Overall health-related quality of life of the subjects was good (mean utility ranged from 0.68 (±0.08) to 0.85(±0.14) over the nine utility measures) and comparable to patients without diabetes. Summary indices were well correlated with each other (r = 0.76 to 0.99), and showed lower health-related quality of life in patients with major diabetes-related events such as stroke or myocardial infarction. Despite the smaller number of items used in the scoring of the EQ-5D, it generally performed at least as well as SF-36 based methods. However, all utility measures had some limitation such as limited range or ceiling effects. Conclusion: The summary utility measures showed good agreement, and showed good discrimination between major and minor health state changes. However, EQ-5D based measures performed as well and a
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