Comparison of SF-6D and EQ-5D scores in patients with breast cancer

Background: Utility values are a key component of a cost-utility analysis. The EQ-5D and SF-6D are two commonly used measures for deriving utilities. Of particular importance is assessing the performance of these instruments in terms of validity. Objectives: This study aimed to compare the performance of the EQ-5D and the SF-6D in different states of breast cancer. Patients and Methods: This was a cross-sectional study of 163 patients with breast cancer who attended the breast cancer subspecialty clinic affiliated with the breast cancer research center (BCRC) at ACECR, in Tehran, Iran, and were consecutively recruited. Patients completed several questionnaires, including the EQ-5D, SF-36, and general questions regarding their demographic characteristics. Utility values for different states of breast cancer were obtained using predetermined algorithms for the EQ-5D and SF-6D. The distribution of the utility values and the differences between the different states for both instruments were statistically assessed. Furthermore, the agreement between the two instruments was evaluated using intra-class correlation coefficients and Bland-Altman plots. Results: The mean and median EQ-5D utility scores for the total sample were 0.685 and 0.761, respectively. The mean SF-6D utility score for the total sample was 0.653, and the median utility score was 0.640. The mean utility values of the EQ-5D for “state P,” “state R,” “state S,” and “state M” were estimated as 0.674, 0.718, 0.730, and 0.552, respectively. The SF-6D provided mean utility values of 0.638, 0.677, 0.681, and 0.587 for those states. Both instruments assigned statistically significant (P < 0.01) scores for different states. The intra-class correlation for the two measures was 0.677 (95% confidence interval (CI): 0.558 - 0.764). The Bland-Altman plot indicated a better agreement on the higher values and that at higher values, the EQ-5D yields a higher score than the SF-6D; this relationship was reversed at lower values. Conclusions: Although the two instruments were able to discriminate between various states, the values derived from these instruments were quite different. This distinction could have influenced the conclusions of an economic evaluation. Further research is required to determine which instrument should be used in economic evaluations.