METHODS: The impact of omalizumab was estimated through a one-year static cohort model using the Work Productivity and Activity Impairment Allergy Specific (WPAI-AS) questionnaire derived from a clinical trial on omalizumab enrolling patients with severe and most severe JCP symptoms, which had been conducted in Japan. This effect was quantified using Japanese official statistics on employment and time use. The human capital approach and the proxy good approach were employed to monetize paid and unpaid work activities, respectively. A sensitivity analysis was implemented to account for modeling structural uncertainties.
RESULTS: Our results show that the use of omalizumab might reduce the paid and unpaid work productivity losses due to severe and most severe JCP by nearly one-third. In the severe symptom period of three weeks, 36.6 million hours of lost paid and unpaid work hours could be avoided, which sums up to a monetized productivity loss of 728.3 million USD.
CONCLUSIONS: Omalizumab could provide substantial benefits in terms of paid and unpaid work activities in patients with severe and most severe JCP. Our results also highlight the importance of considering unpaid work in estimating productivity costs due to poor health.
METHODS: In the EQ-VT protocol, 196 pairs of EQ-5D-5L health states were valued by a general population sample using DCE method for all studies. DCE data were obtained from the study PI. To understand how the health preferences are different/similar with each other, the following analyses were done: (1) the statistical difference between the coefficients; (2) the relative importance of the five EQ-5D dimensions; (3) the relative importance of the response levels.
RESULTS: The number of statistically differed coefficients between two studies ranged from 2 to 16 (mean: 9.3), out of 20 main effects coefficients. For the relative importance, there is not a universal preference pattern that fits all studies, but with some common characteristics, e.g. mobility is considered the most important; the relative importance of levels are approximately 20% for level 2, 30% for level 3, 70% for level 4 for all studies.
DISCUSSION: Following a standardized study protocol, there are still considerable differences in the modeling and relative importance results in the EQ-5D-5L DCE data among 11 Asian studies. These findings advocate the use of local value set for calculating health state utility.