Informing Structural Assumptions for Three State Oncology Cost-Effectiveness Models through Model Efficiency and Fit

Area of Science:

• Health economics
• Mathematical modeling
• Oncology

Background:

• Partitioned survival models (PSMs) and state transition models (STMs) are used for oncology cost-effectiveness, but model choice often lacks clear justification.
• Existing economic modeling guidelines emphasize structure selection based on disease, data, and decision problems, yet multiple structures are rarely compared.
• A lack of tools hinders the evaluation of internal validity measures like model fit and efficiency for different structural choices.

Purpose of the Study:

• To present methods and an R software package (psm3mkv) for evaluating the fit and efficiency of different model structures.
• To address the gap in readily available tools for comparing model structures in cost-effectiveness analysis.
• To aid modelers in assessing structural uncertainties and sensitivities.

Main Methods:

• Evaluation of model fit and efficiency for three distinct model structures.
• Application of methods using interim and final analysis datasets from the KEYNOTE-826 randomized controlled trial.
• Utilizing the accompanying R software package, psm3mkv, for analysis.

Main Results:

• The State Transition Model (STM) Clock Reset structure exhibited the best and most efficient fit at both interim and final analyses.
• Structural uncertainties were reduced from the interim to the final analysis.
• The developed methods facilitate easier evaluation and reporting of model fit and efficiency.

Conclusions:

• The STM Clock Reset structure is recommended for the analyzed oncology cost-effectiveness model based on fit and efficiency.
• The presented methods and software enhance the ability to assess internal validity and structural assumptions.
• Modelers can better evaluate structural choices, implicit assumptions, and sensitivities, aligning with best practices in health economic modeling.