Economic EvaluationUsing Metamodeling to Identify the Optimal Strategy for Colorectal Cancer Screening
Highlights
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Although metamodels have been used to reduce computational burden of advanced analyses with simulation models across several disciplines, lacking applications within health economics impede the uptake of metamodeling methods that could support computationally demanding analyses, such as value of information analysis, and the application of optimization algorithms.
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This study illustrates the use of metamodels to negate the computational challenges of running a complex simulation model, allowing for optimization of the Dutch colorectal cancer screening program, rather than selecting a good program using the traditional approach of evaluating only a limited set of strategies.
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Metamodels can be used to perform analyses that otherwise could not have been performed with computationally demanding health economics simulation models, which may result in important insights that can support decision making and provide additional information on the characteristics and validity of such simulation models.
Abstract
Objectives
Metamodeling can address computational challenges within decision-analytic modeling studies evaluating many strategies. This article illustrates the value of metamodeling for evaluating colorectal cancer screening strategies while accounting for colonoscopy capacity constraints.
Methods
In a traditional approach, the best screening strategy was identified from a limited subset of strategies evaluated with the validated Adenoma and Serrated pathway to Colorectal CAncer model. In a metamodeling approach, metamodels were fitted to this limited subset to evaluate all potentially plausible strategies and determine the best overall screening strategy. Approaches were compared based on the best screening strategy in life-years gained compared with no screening. Metamodel runtime and accuracy was assessed.
Results
The metamodeling approach evaluated >40 000 strategies in <1 minute with high accuracy after 1 adaptive sampling step (mean absolute error: 0.0002 life-years) using 300 samples in total (generation time: 8 days). Findings indicated that health outcomes could be improved without requiring additional colonoscopy capacity. Obtaining similar insights using the traditional approach could require at least 1000 samples (generation time: 28 days). Suggested benefits from screening at ages <40 years require adequate validation of the underlying Adenoma and Serrated pathway to Colorectal CAncer model before making policy recommendations.
Conclusions
Metamodeling allows rapid assessment of a vast set of strategies, which may lead to identification of more favorable strategies compared to a traditional approach. Nevertheless, metamodel validation and identifying extrapolation beyond the support of the original decision-analytic model are critical to the interpretation of results. The screening strategies identified with metamodeling support ongoing discussions on decreasing the starting age of colorectal cancer screening.