Estimating the Unknown Parameters of the Natural History of Metachronous Colorectal Cancer Using Discrete-Event Simulation

Author:

Erenay Fatih Safa123,Alagoz Oguzhan123,Banerjee Ritesh123,Cima Robert R.123

Affiliation:

1. Department of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, Wisconsin (Department of Management Sciences, University of Waterloo Waterloo (FSE); OA)

2. Formerly at Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota. Current affiliation is Analysis Group, Inc., Boston, Massachusetts (RB)

3. Colon and Rectal Surgery, Mayo Graduate School of Medicine, Mayo Clinic, Rochester, Minnesota (RRC)

Abstract

Objectives. Some aspects of the natural history of metachronous colorectal cancer (MCRC), such as the rate of progression from adenomatous polyp to MCRC, are unknown. The objective of this study is to estimate a set of parameters revealing some of these unknown characteristics of MCRC. Methods. The authors developed a computer simulation model that mimics the progression of MCRC for a 5-year period following the treatment of primary colorectal cancer (CRC). They obtained the inputs of the simulation model using longitudinal data for 284 CRC patients from the Mayo Clinic, Rochester. Results. Five-year MCRC incidence and all-cause mortality were 7.4% and 12.7% in the patient cohort, respectively. Statistical analysis showed that 5-year MCRC incidence was associated with gender ( P = 0.05), whereas both all-cause and CRC-related mortalities were associated with age ( P < 0.001 and P = 0.01). Estimated annual probabilities of progression from adenomatous polyp to MCRC and from MCRC to metastatic MCRC were 0.14 and 0.28, respectively. Annual probabilities of mortality after MCRC and metastatic MCRC treatments were estimated to be 0.06 and 0.26, respectively. The estimated annual probability of mortality due to undetected MCRC was 0.16. Conclusions. The results imply that MCRC, especially in women, may be more common than suggested by previous studies. In addition, statistics derived from the clinical data and results of the simulation model indicate that gender and age affect the progression of MCRC.

Publisher

SAGE Publications

Subject

Health Policy

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