Abstract
BACKGROUND: Patients with well-managed rare chronic diseases such as hemophilia maintain a stable health state and health-related quality of life (HrQoL) that may be affected by acute events. Longitudinal HrQoL assessments analyzed using multivariate multilevel (MVML) modelling can determine the impact of such events on individuals (within-person effect) and identify factors influencing within-population differences (between-person effect). OBJECTIVES: To demonstrate the application of MVML modelling in a longitudinal study of HrQoL in hemophilia A. METHODS/DESIGN/PARTICIPANTS: Using data on 136 adults and 125 children from a two-year observational cohort study of burden of illness in US hemophilia A patients, MVML modelling determined the effect of time-invariant (sociodemographic and clinical characteristics) and time-varying factors (bleeding frequency, emergency room visits, and missed work/school days) on within-person and between-person HrQoL changes. HrQoL was assessed using the SF-12 health survey (adults) and PedsQL inventory (children) at baseline, then every 6 months. RESULTS: In children, within-person (p < 0.0001) and between-person (p < 0.0001) psychosocial functioning was reduced by each additional bleed and missed day (within-person: p = 0.0089; between-person: p = 0.0060). Within-person physical functioning was reduced by each additional bleed (p < 0.0001), emergency room (ER) visit (p = 0.0284), and missed day (p = 0.0473). Between-persons, additional missed days (p < 0.0001) significantly decreased physical functioning. In adults, each additional missed day reduced SF-12 Health Survey mental (p = 0.0025) and physical (p = 0.0093) component summary scores. Each additional bleed also decreased physical component summary (PCS) significantly (p = 0.0093). CONCLUSIONS: This study demonstrated the applicability of MVML modelling in identifying time-invariant and time-varying factors influencing HrQoL in a rare chronic disease population. Small but significant within-person and between-person changes in HrQoL with each additional acute event experienced were identified, which if frequent, could have a large cumulative impact. The results suggest that MVML modelling may be applied to future studies of longitudinal change in HrQoL in other rare chronic disease populations.