P57 Mapping Quality of Life - Alzheimer's Disease (QOL-AD) Scores to EQ-5D-5L Utilities in the Ambar Trial Population

Health state utilities are required to model the cost/benefit of novel treatments in accordance with Health Technology Assessment guidelines. The AMBAR phase 2b/3 trial (NCT01561053) evaluated the efficacy and safety of plasma exchange with albumin replacement in mild-to-moderate Alzheimer’s disease (AD) patients. Health-related quality of life was measured through the disease-specific Quality of Life - Alzheimer’s disease (QoL-AD) questionnaire. EQ-5D-5L utilities were estimated from AMBAR QoL-AD data using a validated mapping algorithm developed by Rombach et al. (2020). A multinomial logistic regression model was employed to generate mapped utility values for the placebo and pooled treatment arms for both patient and proxy-rated QoL-AD scores. The model included age and sex as covariates and was run including QoL-AD item 7 (marriage). The UK value set (crosswalk to EQ-5D-3L value set by van Hout et al. 2012) was applied. The analysis sample included 298 patients and 298 caregivers with complete baseline QoL-AD data (i.e., all 13-items completed). The mean mapped patient-rated EQ-5D-5L utility at final visit was 0.8132 for placebo and 0.8312 for pooled treatment. For proxy-raters, the mean mapped EQ-5D-5L utility at final visit was 0.7333 for placebo and 0.7235 for pooled treatment. The correlation between observed QoL-AD scores and mapped EQ-5D-5L utilities was 0.526 for patients and 0.552 for proxies, in line with the findings in Rombach et al. (2020). Mapped EQ-5D-5L utilities were estimated for the AMBAR population. The estimates were relatively consistent at final visit across treatment arms. However, the correlation between observed QoL-AD scores and mapped EQ-5D-5L scores remained moderate. This may indicate a general lack of conceptual overlap in the domains covered by the QoL-AD and the EQ-5D-5L, limiting the precision of a mapping approach and reinforcing the benefit of directly collecting utilities in AD trials for increased accuracy of estimates.