Abstract
OBJECTIVE: This study constructs, calibrates, and verifies a mathematical simulation model designed to project the natural history of ESCC and is intended to serve as a platform for testing the benefits and cost-effectiveness of primary and secondary ESCC prevention alternatives. METHODS: The mathematical model illustrates the natural history of ESCC as a sequence of transitions among health states, including the primary health states (e.g., normal mucosa, precancerous lesions, and undetected and detected cancer). Using established calibration approaches, the parameter sets related to progression rates between health states were optimized to lead the model outputs to match the observed data (specifically, the prevalence of precancerous lesions and incidence of ESCC from the published literature in Chinese high-risk regions). As illustrative examples of clinical and policy application, the calibrated and validated model retrospectively simulate the potential benefit of two reported ESCC screening programs. RESULTS: Nearly 1,000 good-fitting parameter sets were identified from 1,000,000 simulated sets. Model outcomes had sufficient calibration fit to the calibration targets. Additionally, the verification analyses showed reasonable external consistency between the model-predicted effectiveness of ESCC screening and the reported data from clinical trials. CONCLUSIONS: This parameterized mathematical model offers a tool for future research investigating benefits, costs, and cost-effectiveness related to ESCC prevention and treatment.