Application and cross-cultural validation of the ASAS HI-based health state utility algorithm in Chinese patients with spondyloarthritis

Health State Utility (HSU) reflects individual preferences for specific health states and serve as a core parameter in health economic evaluations. Spondyloarthritis (SpA), a group of rheumatic diseases characterized by chronic back pain and joint involvement, imposes a substantial disease burden due to its progressive functional impairment and high healthcare costs. Accurate assessment of HSU in SpA patients is essential for a comprehensive understanding of disease burden, the development of targeted treatment strategies, and the optimization of healthcare resource allocation. A SpA-specific HSU algorithm based on the Assessment of Spondyloarthritis international Society Health Index (ASAS HI) has been developed and preliminarily validated in several European countries, yet no empirical studies have examined its applicability in China. Therefore, the aim of this study was to determine the applicability of this HSU algorithm to Chinese patients with SpA, and to assess its consistency with the Time Trade-Off (TTO) method and the Five-Level EuroQoL five dimensions (EQ-5D-5 L), providing methodological support for health economic evaluations in this population. The study involved 102 SpA patients. Health state utility values (HSUVs) were assessed using the TTO, EQ-5D-5 L, and ASAS HI algorithms, respectively. Descriptive statistics were performed, followed by evaluations of convergent and discriminant validity for the ASAS HI algorithm. Consistency among these methods was tested using Bland-Altman analysis, ICC, and linear regression models. Finally, a sensitivity analysis was conducted through age stratification to further verify the robustness of the results. HSUVs calculated by different algorithms ranged from 0.67 to 0.78. The HSUV derived from ASAS HI was significantly positive correlated with TTO and EQ-5D-5 L score, which has low correlation with unrelated variables. Bland-Altman analysis showed that most differences fell within ± 1.96 standard deviations. The ICC exceeded 0.7, and the coefficient of determination for the linear regression model was 0.63 and 0.80, respectively. Sensitivity analysis also indicated that the research results have good stability among different age groups. The ASAS HI-based HSUV algorithm demonstrates good validity and high consistency with TTO and EQ-5D-5 L in Chinese SpA patients. It can serve as a reliable tool for HSUV assessment in this population.