Evaluating The Addition To Formulary of Belimumab For The Treatment of Systemic Lupus Erythematosus: A Cost-Effectiveness Model

Abstract

Systemic lupus erythematosus (SLE) is a chronic, multisystem autoimmune disease that causes potentially irreversible organ damage. A previous cost-effectiveness model (CEM) evaluating intravenous belimumab in SLE was a patient microsimulation model with a series of risk equations describing disease activity and survival models to depict time to organ damage. This model was substantially revised to use a semi-Markov model that still captures the complexity of SLE and analyses subcutaneous belimumab. Post hoc regression analyses of the intravenous belimumab US long-term extension study (BEL112233) and the Toronto Lupus Cohort were conducted to identify drivers of utilities, disease progression and SLE-related mortality (HO-15-15879/206347). Costs were based on LUCIC (Systemic LUpus Erythematosus Cost of Care in Canada; 114745). Results demonstrated that the Systemic Lupus International Collaborating Clinics/American College of Rheumatology Damage Index (SDI) and the presence of cardiovascular damage were sufficient to capture organ damage effects. Thus, health states were defined by treatment, SDI score and presence/absence of cardiovascular damage. The model uses a 1-year cycle length to analyse over a modifiable lifetime time horizon. Patient distribution at time=0 and Year 1 outcomes are based on source clinical trials. Thereafter, disease activity measured by adjusted mean SLEDAI (AMS), flares, and probability of organ damage progression are modelled separately for each health state and dynamically updated each cycle. Health state costs and utilities are based on multivariate regression analyses that increment payoffs for each cycle. A new CEM framework was developed within a Markov model, which further allowed incorporation of AMS, flares and organ damage progression in SLE. Total costs and outcomes were similar to the previous CEM. This modelling study has simplified clinical assumptions of SLE to produce a Markov model that may be used by additional stakeholders due to its increased transparency and shorter run time. Study funded by GSK.