Estimating the unknown parameters of the natural history of metachronous colorectal cancer using discrete-event simulation

Fatih Safa Erenay, Oguzhan Alagoz*, Ritesh Banerjee, Robert R. Cima

*Corresponding author for this work

Research output: Contribution to journalArticle

17 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)611-624
Number of pages14
JournalMedical Decision Making
Volume31
Issue number4
DOIs
StatePublished - Jul 1 2011
Externally publishedYes

Keywords

  • colorectal cancer
  • discrete event simulation
  • operations research
  • simulation methods

ASJC Scopus subject areas

  • Health Policy

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