Abstract

Systemic lupus erythematosus (SLE) has a complex and heterogeneous natural history. Our aim was to develop a conceptual model of SLE that characterizes the relationships between short- and long-term outcomes that could be applied in future economic evaluations and health technology assessments of new therapies. As per the ISPOR-SMDM Modeling Good Research Practices Task Force guidelines, a targeted literature review was conducted to identify any previously developed conceptual or economic models in SLE. A steering committee of clinical and economic experts was convened to review existing model frameworks and brainstorm a new conceptual model, building on revision and refinement of prior models. The relationships between patient characteristics, disease activity, commonly used treatments, organ damage, health-related quality of life (HRQoL), and mortality were all considered by the committee, as well as the likely data available to parameterize the model in the future. Based on the existing literature and consensus among committee members, the key components of the conceptual model included disease activity, corticosteroid use, and organ damage by individual system. Relationships not present in prior models included stratifying short-term disease activity by level (e.g., low, moderate, high)and corticosteroid use influencing subsequent disease activity. Higher disease activity levels (i.e., flare) would trigger higher short-term corticosteroid use and increased risk of long-term organ damage. Higher doses of corticosteroids should decrease disease activity in the short-term, while raising the risk of long-term organ damage. Relevant covariates identified included demographics, age at onset, cardiovascular comorbidities, baseline organ damage, history of lupus nephritis, and anti-malarial/other immunosuppressant use. Long-term outcomes include organ damage, mortality, HRQoL, and costs. By linking short- and long-term outcomes, this conceptual model provides a foundation on which to conduct future economic evaluations of new SLE therapies. The next step is to conduct a model validation using real world data.

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