OBJECTIVES:

Migraine is a common neurological disease with substantial impact on patient functioning. Migraine reduces workplace productivity through absenteeism (missed work) and presenteeism (decreased productivity while at work). The objective of this analysis is to quantify the productivity losses of patients enrolled in two pivotal erenumab studies by linking numbers of absenteeism and presenteeism days to monthly migraine days (MMD).

METHODS:

Patient-level data from the two pivotal erenumab studies in episodic migraine (EM; NCT02456740) and chronic migraine (CM; NCT02066415) were pooled, including versions of the migraine disability assessment (MIDAS) questionnaire, assessing the number of days on which productivity was affected by migraine over the previous 4 weeks (EM) or 12 weeks (CM). Separate questions addressed missed days of work (absenteeism days) and days of work with productivity reductions of 50% or more (presenteeism days). Longitudinal, non-linear, hierarchical, zero-inflated Poisson regression models were fitted between the productivity outcomes and MMD, adjusting for age, sex, race, treatment group (erenumab 140mg and placebo), prior treatment use and baseline MMD. Zero-inflated models were chosen due to the high proportion of patients who reported no productivity losses, regardless of their MMD. The expected number of absenteeism and presenteeism days were estimated using the Delta method.

RESULTS:

Patients with 14 MMD lost a predicted 1.332 (95% CI: 1.329–1.335) and 3.651 (3.638–3.664) days of absenteeism and presenteeism, respectively. Patients experiencing migraine every day (28 MMD) lost a predicted 2.801 (2.795–2.807) and 10.587 (10.548–10.625) days of absenteeism and presenteeism, respectively.

CONCLUSIONS:

Migraine imposes a significant productivity burden on patients, which translates to a substantial financial impact, in addition to the direct medical costs of migraine. Linking productivity endpoints to MMD allows the estimation of potential savings of effective migraine prevention. The analysis has important applications in supporting the economic evaluation of migraine preventives.