A Systematic Review of Decision-Analytic Models for Evaluating Cost-Effectiveness of Asthma Interventions

To demonstrate the landscape of model-based economic studies in asthma and highlight where there is room for improvement in the design and reporting of studies.

A systematic review of the methodologies of model-based, cost-effectiveness analyses of asthma-related interventions was conducted. Models were evaluated for adherence to best-practice modeling and reporting guidelines and assumptions about the natural history of asthma.

A systematic search of English articles was performed in MEDLINE, EMBASE, and citations within reviewed articles. Studies were summarized and evaluated based on their adherence to the Consolidated Health Economic Evaluation Reporting Standards (CHEERS). We also studied the underlying assumptions about disease progression, heterogeneity in disease course, comorbidity, and treatment effects.

Forty-five models of asthma were included (33 Markov models, 10 decision trees, 2 closed-form equations). Novel biological treatments were evaluated in 12 studies. Some of the CHEERS' reporting recommendations were not satisfied, especially for models published in clinical journals. This was particularly the case for the choice of the modeling framework and reporting on heterogeneity. Only 13 studies considered any subgroups, and 2 explicitly considered the impact of comorbidities. Adherence to CHEERS requirements and the quality of models generally improved over time.

It would be difficult to replicate the findings of contemporary model-based evaluations of asthma-related interventions given that only a minority of studies reported the essential parameters of their studies. Current asthma models generally lack consideration of disease heterogeneity and do not seem to be ready for evaluation of precision medicine technologies.