An evidence-based microsimulation model for colorectal cancer: validation and application.
BACKGROUND
The Colorectal Cancer Simulated Population model for Incidence and Natural history (CRC-SPIN) is a new microsimulation model for the natural history of colorectal cancer that can be used for comparative effectiveness studies of colorectal cancer screening modalities.


METHODS
CRC-SPIN simulates individual event histories associated with colorectal cancer, based on the adenoma-carcinoma sequence: adenoma initiation and growth, development of preclinical invasive colorectal cancer, development of clinically detectable colorectal cancer, death from colorectal cancer, and death from other causes. We present the CRC-SPIN structure and parameters, data used for model calibration, and model validation. We also provide basic model outputs to further describe CRC-SPIN, including annual transition probabilities between various disease states and dwell times. We conclude with a simple application that predicts the impact of a one-time colonoscopy at age 50 on the incidence of colorectal cancer assuming three different operating characteristics for colonoscopy.


RESULTS
CRC-SPIN provides good prediction of both the calibration and the validation data. Using CRC-SPIN, we predict that a one-time colonoscopy greatly reduces colorectal cancer incidence over the subsequent 35 years.


CONCLUSIONS
CRC-SPIN is a valuable new tool for combining expert opinion with observational and experimental results to predict the comparative effectiveness of alternative colorectal cancer screening modalities.


CONCLUSIONS
Microsimulation models such as CRC-SPIN can serve as a bridge between screening and treatment studies and health policy decisions by predicting the comparative effectiveness of different interventions. As such, it is critical to publish model descriptions that provide insight into underlying assumptions along with validation studies showing model performance.
Rutter
Carolyn M
CM
Group Health Research Institute, 1630 Minor Avenue, Seattle, WA 98101, USA. rutter.c@ghc.org
Savarino
James E
JE
D000236:Adenoma / Q000175:diagnosis* / Q000453:epidemiology; D000368:Aged; D000369:Aged, 80 and over; D002277:Carcinoma / Q000175:diagnosis* / Q000453:epidemiology; D003113:Colonoscopy; D015179:Colorectal Neoplasms / Q000175:diagnosis* / Q000453:epidemiology; D003198:Computer Simulation; D055088:Early Detection of Cancer / Q000379:methods*; D019317:Evidence-Based Medicine; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D015203:Reproducibility of Results; D012306:Risk