Comparison of Contemporaneous EQ-5D and SF-6D Responses Using Scoring Algorithms Derived from Similar Valuation Exercises

Objectives: Poor agreement between preference-based health-related quality-of-life instruments has been widely reported across patient and community-based samples. This study compares index scores generated from contemporaneous EQ-5D (3-level version) and SF-6D (SF-36 version) responses using scoring algorithms derived from independently-conducted Australian population-representative discrete choice experiments (DCEs), providing the first comparative analysis of health state valuations using the same method of valuation across the full value sets. Methods: EQ-5D and SF-6D responses from seven patient data sets were transformed into health state valuations using published DCE-derived scoring algorithms. The empirical comparative evaluation consisted of graphical illustration of the location and spread of index scores, reporting of basic descriptive statistics, exploration of between-measure differences in mean index scores, and analysis of agreement. Results: Compared with previously published findings regarding the comparability of "conventional" EQ-5D and SF-6D index scores, health state valuations from the DCE-derived scoring procedures showed that agreement between scores remained "fair" (intraclass correlation coefficient values across the seven data sets ranged from 0.375 to 0.615). Mean SF-6D scores were significantly lower than the respective mean EQ-5D score across all patient groups (mean difference for the whole sample = 0.253). Conclusions: The magnitude of disagreement previously reported between EQ-5D and SF-6D index scores is not ameliorated through the application of DCE-derived value sets; sizeable discrepancies remain. These findings suggest that differences between EQ-5D and SF-6D index scores persist because of their respective descriptive systems. Further research is required to explore the implications of variations in the descriptive systems of preference-based instruments.