Generating Evidence to Inform Health Technology Assessment of Treatments for Systemic Lupus Erythematosus: A Systematic Review of Decision-analytic Model-based Economic Evaluations

Objective
To understand and appraise the approaches taken to handle the complexities of a multi-system disease in published decision-analytic model-based economic evaluations of treatments for systemic lupus erythematosus (SLE).

Methods
A systematic review was conducted to identify all published model-based economic evaluations of treatments for SLE. Treatments that were considered for inclusion comprised anti-malarial agents, immunosuppressive therapies, and biologics including rituximab and belimumab. Medline and Embase were searched electronically from inception until September 2018. Titles and abstracts were screened against the inclusion criteria by two reviewers; agreement between reviewers was calculated according to Cohen’s kappa. Pre-defined data extraction tables were used to extract the key features, structural assumptions, and data sources of input parameters from each economic evaluation. The completeness of reporting for the methods of each economic evaluation was appraised according to the Consolidated Health Economics Reporting Standards (CHEERS) statement.

Results
Six decision-analytic model-based economic evaluations were identified. The studies included azathioprine (n=4), mycophenolate mofetil (n=3), cyclophosphamide (n=2), and belimumab (n=1) as relevant comparator treatments; no economic evaluation estimated the relative costeffectiveness of rituximab. Six items of the CHEERS statement were reported incompletely across the sample: target population, choice of comparators, measurement and valuation of preference-based outcomes, estimation of resource use and costs, choice of model, and the characterization of heterogeneity.

Conclusions
Complexity in the diagnosis, management, and progression of disease can make decisionanalytic model-based economic evaluations of treatments for SLE a challenge to undertake. The findings from this study can be used to improve the relevance of model-based economic evaluations in SLE and as an agenda for research to inform future health technology assessment decision-making.