PRM88 - Estimating Patient Utility in Migraine: Longitudinal Analysis of Erenumab Clinical Trial Data

Abstract

Migraine is a debilitating disease with substantial impact on patients’ health-related quality of life (HRQoL). Cost-utility analysis of migraine preventives requires the estimation of patient utility values and how these relate to monthly migraine days (MMD). The objective of this analysis is to model utility values in a longitudinal framework, allowing more accurate estimates of expected utility values. Data from two pivotal erenumab studies in episodic migraine (EM; NCT02456740) and chronic migraine (CM; NCT02066415) were pooled to analyze HRQoL outcomes. Migraine Specific Questionnaire (MSQ) version 2.1 and Headache Impact Test (HIT-6) condition-specific instruments were mapped to the EQ-5D using published mapping algorithms (Gillard et al. 2012) to generate generic, preference-based utility estimates, suitable for use in economic models. Longitudinal non-linear beta regressions were fitted between mapped EQ-5D utility values, MMD and treatment group (erenumab 140mg and placebo), adjusting for age, sex, race and baseline MMD in the various time periods considered. Expected utility values by MMD were calculated using the Delta method. Multilevel linear models and fractional response models with probit and logit links were also assessed. The analysis sample included data from 1,113 patients; 83.7% females with a mean age of 41.6 years. The longitudinal beta regression models closely approximated the observed utility values. Patients with 14 MMD were predicted to have MSQ mapped mean utility values of 0.608 (95% CI: 0.595–0.621) for patients treated with erenumab 140mg and 0.590 (0.577–0.602) for patients receiving placebo. The respective predicted HIT-6 mapped mean utility values were 0.698 (0.654–0.741) and 0.659 (0.629–0.689). Mapped utility values for erenumab patients were consistently higher than placebo patients with the same number of MMD. Linking patient QoL to MMD allows utility estimates for different levels of MMD to be predicted, for use in economic evaluations of preventive therapies.