Different Frameworks, Similar Results? Head-to-Head Comparison of the Generic Preference-Based Health-Outcome Measures CS-Base and EQ-5D-5L.

Objective: We compared two generic, preference-based health-outcome measures: the novel patient-centered Château-Santé Base (CS-Base), entailing a multi-attribute preference response framework, and the widely used EQ-5D-5L, regarding effects of different measurement frameworks and different descriptive systems.

Methods: We conducted a cross-sectional study using a random sample of patients (3019 reached, 1988 included) in the USA with various health conditions. The CS-Base (12 attributes, each with four levels), EQ-5D-5L and the 5D-4L (an ad hoc, multi-attribute preference response-based measure that includes five attributes similar to the EQ-5D-5L, but with four levels) were used as health-outcome measures. We compared the proportions of problems reported on health attributes, statistical robustness and face validity of coefficients, attribute importance, differentiation between health states based on health-state values obtained with these measures, and user experience.

Results: All the CS-Base and 5D-4L coefficients had logical orders and significant differences from the reference level (p < 0.001). Substantial differences were observed in the CS-Base and 5D-4L coefficients between all levels on all attributes, while subtle differences were seen in those of the EQ-5D-5L. Attribute importance of usual (daily) activities were lowest or second lowest in all the three health-outcome measures. Attributes with the highest importance in the CS-Base, 5D-4L, and EQ-5D-5L were respectively mobility, anxiety/depression, and pain/discomfort. Four attributes are similar between the CS-Base and EQ-5D-5L, eight are exclusive to CS-Base. Of the eight, vision and hearing had the highest importance. Health-state values showed a smoother distribution with minimal discontinuity in the CS-Base and EQ-5D-5L than in the 5D-4L. In user experience evaluation, both CS-Base and the 5D-4L showed mean scores above 50 (indicating positive evaluation) in terms of the description of health and ease of understanding.

Conclusions: This study demonstrated that CS-Base and 5D-4L, which are grounded in the multi-attribute preference response framework, produced statistically robust coefficients, with better face validity than those for the EQ-5D-5L. CS-Base and the EQ-5D-5L outperformed the 5D-4L in differentiating between health states. Notwithstanding differences in content, measurement frameworks, and estimated coefficients, the computed health-state values were similar between CS-Base and EQ-5D-5L.