OBJECTIVES: Achondroplasia is a rare genetic disorder that prevents the changing of cartilage to bone, leading to disproportionate short stature, which can have serious complications that impact quality of life. The aim of this study is to elicit health state utility values (HSUV) corresponding to health states describing the burden of achondroplasia, via a TTO valuation approach with the general public.

METHODS: A targeted literature review was undertaken to inform the health state descriptions, which were validated by clinical experts(n=2) and patient advocates(n=2) via semi-structured interviews. Ten health states were defined, with a pair of health states (no-complications or complications) created for each of the following age groups: up to2 years(HS1), 2-4 years(HS2), 5-14 years(HS3), 15-18 years(HS4) and 18+(HS5). A composite time trade-off (cTTO) exercise was undertaken based on the valuation study protocol v2.1 for the EQ-5D-5L instrument. The study was conducted face-to-face with a moderator in the UK and US. Descriptive statistics were computed for HSUV, and the difference in mean utility values within the health state pairs was tested via paired t-tests.

RESULTS: In total, 420 respondents were recruited; after quality checks, the analysis sample was n=354. The highest HSUVs were for the two youngest states (HS1;HS2), without complications, with mean values of 0.73(SD;0.39) and 0.76(SD;0.34), respectively. The lowest mean HSUVs were for the two oldest patient states, with complications (HS4;HS5), eliciting mean values of 0.55(SD;0.36) and 0.55(SD;0.34), respectively. Differences within age group pairs between no complications and complications were notable, with patient health states differences showing statistical significance (at p<0.05).

CONCLUSIONS: Overall, clear differences between HSUVs were seen between age groups with complications reducing the mean utility valuations. The study also showed HSUVs were lower when compared to average stature population. This study may be used further in economic models that estimate the value of treatments for achondroplasia.