Microsimulation Model for Prevention and Intervention of Coloretal Cancer in China (MIMIC-CRC): Development, Calibration, Validation, and Application

Abstract

Introduction: A microsimulation model provides important references for decision-making regarding colorectal cancer (CRC) prevention strategies, yet such a well-validated model is scarce in China.

Methods: We comprehensively introduce the development of MIcrosimulation Model for the prevention and Intervention of Colorectal Cancer in China (MIMIC-CRC). The MIMIC-CRC was first constructed to simulate the natural history of CRC based on the adenoma-carcinoma pathway. The parameters were calibrated and validated using data from population-based cancer registry data and CRC screening programs. Furthermore, to assess the model's external validity, we compared the model-derived results to outcome patterns of a sigmoidoscopy screening trial in the UK [UK Flexible Sigmoidoscopy Screening (UKFSS) trial]. Finally, we evaluated the application potential of the MIMIC-CRC model in CRC screening by comparing the 8 different strategies.

Results: We found that most of the model-predicted colorectal lesion prevalence was within the 95% CIs of observed prevalence in a large population-based CRC screening program in China. In addition, model-predicted sex- and age-specific CRC incidence and mortality were equivalent to the registry-based data. The hazard ratios of model-estimated CRC-related incidence and mortality for sigmoidoscopy screening compared to no screening were 0.60 and 0.51, respectively, which were comparable to the reported results of the UKFSS trial. Moreover, we found that all 8 strategies could reduce CRC incidence and mortality compared to no screening.

Conclusions: The well-calibrated and validated MIMIC-CRC model may represent a valid tool to assess the comparative effectiveness of CRC screening strategies and will be useful for further decision-making to CRC prevention.

Keywords: Markov model; colorectal cancer; microsimulation model; natural history; screening.

Figure 1

Concept framework and analysis flow. (A) Model analysis diagram. (B) Flowchart of the natural history model for the adenoma-carcinoma sequence. Solid lines represent the progression of colorectal lesions through the adenoma-carcinoma sequence in the absence of screening; dashed lines show the movement between states because of the detection and removal of adenoma, the detection of asymptomatic colorectal cancer by screening or symptom, and the curation of colorectal cancer. CRC, colorectal cancer; FS, flexible sigmoidoscopy; FIT, fecal immunochemical test.

Figure 2

Comparison of model-predicted prevalence of colorectal lesions with the observed results in China. (A) prevalence of colorectal cancer; (B) prevalence of advanced adenoma; (C) prevalence of non-advanced adenoma; (D) any advanced neoplasm.

Figure 3

Ratios and corresponding CI of model-predicted incidence and mortality of colorectal cancer with the registry-based estimations in China in 2015. Dashed lines show the margin of testing for equivalence (0.2). GBD, global burden of disease. (A) incidence ratios by model vs. GBD estimation in both sexes; (B) mortality ratios by model vs. GBD estimation in both sexes; (C) incidence ratios by model vs. GBD estimation in men; (D) mortality ratios by model vs. GBD estimation in men; (E) incidence ratios by model vs. GBD estimation in women; (F) mortality ratios by model vs. GBD estimation in women.

Figure 4

The prevalence trends of colorectal cancer incidence and mortality in all screening strategies compared with no screening. CRC, colorectal cancer; FIT, fecal immunochemical test. (A) cumulative CRC incidence among screening groups; (B) cumulative CRC related mortality among screening groups.