Converting the SF-12 into the EQ-5D: an empirical comparison of methodologies

For cost-utility analysis, analysts need a measure that summarizes health-status utilities in a single index of health-related quality of life (HR-QOL). It is common to find in clinical studies that only an HR-QOL profile measure such as the SF-36 is included, but not the summary HR-QOL index. Therefore, the economist's usual practice is to reprocess the profile data into a single index format. Several 'after-market' tools are available to convert the SF-36 or SF-12 into a single form with or without utility-weighting metric property. However, there has been no consensus with regard to a regression method that should be recommended for such a mapping task.

To report on the performance of different regression methods that have previously been applied to the conversion of SF-12 data in the analysis of a single common dataset. The mapping between the SF-12 and EQ-5D is the focus.

The data were adopted from the Medical Expenditure Panel Survey 2003 where 19 678 adults completed both EQ-5D and SF-12 questionnaires. Four econometric techniques, namely ordinary least squares (OLS), censored least absolute deviation, multinomial logit model and two-part model regressions were investigated together with two main types of model specifications: item-based and summary score-based. The performance of each examined model was judged by various criteria, including its estimated mean, the size of mean absolute error and the number of errors.

Among four compared econometric techniques, OLS regression was the most accurate model in estimating the group mean. Models with item-based model specification performed better than those with summary score-based regardless of the chosen econometric technique. Nevertheless, the accuracy of OLS deteriorates in older and less healthy subgroups. The results also suggested that the two-part model, which addresses the heterogeneity issue, performs better in these vulnerable subgroups.

None of the mapping methods included in the current study are suitable for estimating at the individual level. The methodology exemplified here has wider applicability and might just as readily be applied to other members of the SF family or indeed to other profile measures of HR-QOL. However, it is recommended that a preference-based, single index measure of HR-QOL should be included in the clinical studies for the purpose of economic evaluation.