A comparison of EQ-5D and SF-6D in coronary heart disease patients

A comparison of EQ-5D and SF-6D in coronary heart disease patients

Generic preference based instruments with an accompanying set of population based utility weights are increasingly used in economic evaluations. The development of the SF-6D has prompted researchers to undertake head-to-head comparisons of this approach with the EQ-5D. These studies demonstrated a number of different ways to compare the instruments but raised interesting questions as to whether using alternative econometric methods would also support their findings. Data from a multicentre randomised controlled trial of an intervention for coronary heart disease patients was used to compare the SF-6D and the EQ-5D. Three methods were used: 1) the methods used in previous studies; 2) quantile regression; and 3) a panel data approach exploiting the time variation.

Outcome and Translation

This study assessed the contribution of a method widely used in economics and econometrics as a means of improving understanding of the relationship between quality of life instruments. It showed that that strength of association was dependent on whether health improves or deteriorates. Due to lack of prior information on expected health changes however, the study recommended that researchers should use more than one measure in cost-utility analysis.

HERU researchers involved in this research project: Paul McNamee, M Tinelli, (HERU/Academic Primary Care, University of Aberdeen); J Seymour and A Scott.

External Collaborators: Christine Bond (Academic Primary Care, University of Aberdeen)

Publications

McNamee, P. and Seymour, J. (2005) 'Comparing generic preference-based health-related quality of life measures: advancing the research agenda', Expert Review in Pharmacoeconomics and Outcomes Research, 5(5), 567-581.

Seymour, J., McNamee, P., Scott, A. and Tinelli, M. (2010) 'Shedding new light onto the ceiling and floor? A quantile regression approach to compare EQ-5D and SF-6D responses', Health Economics, 19(6), 683-696.

Tinelli, M., Scott, A., Seymour, J., Ryan, M., Bond, C. and McNamee, P. (2014) 'The Authors’ Reply to Koeser and McCrone: "On the Use and Interpretation of Quantile Regression in Quality-of-Life Research"', PharmacoEconomics, 32(2), 229-230.

Presentations

Seymour, J., McNamee, P., Scott, A., Tinelli, M. and Bond, C. (2007) 'Shedding new light onto the ceiling and floor? A quantile regression approach to compare EQ-5D and SF-6D responses', iHEA, Copenhagen, July 2007.

McNamee P. (2009) 'Detection of ceiling and floor effects: a quantile regression approach', Health Economics Unit, Birmingham, 2009.

McNamee, P. (2010) 'Detection of ceiling and floor effects: a quantile regression approach, School of Health and Related Research, University of Sheffield, March 2010.