2023
DOI: 10.1177/23814683221145701
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Modeling the Natural History and Screening Effects of Colorectal Cancer Using Both Adenoma and Serrated Neoplasia Pathways: The Development, Calibration, and Validation of a Discrete Event Simulation Model

Abstract: Background. Existing colorectal cancer (CRC) screening models mostly focus on the adenoma pathway of CRC development, overlooking the serrated neoplasia pathway, which might result in overly optimistic screening predictions. In addition, Bayesian inference methods have not been widely used for model calibration. We aimed to develop a CRC screening model accounting for both pathways, calibrate it with approximate Bayesian computation (ABC) methods, and validate it with large CRC screening trials. Methods. A dis… Show more

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Cited by 3 publications
(2 citation statements)
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“…The model considers differences in dwell time and rate between the two pathways. Details about DECAS model structure, assumptions, calibration and validation for both natural history and screening effects were published elsewhere ( 19 ). To illustrate the main structure of DECAS model, we have provided a schematic diagram and the CRC natural history parameters in the Supplementary Figure S1 ; Supplementary Table S1 .…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…The model considers differences in dwell time and rate between the two pathways. Details about DECAS model structure, assumptions, calibration and validation for both natural history and screening effects were published elsewhere ( 19 ). To illustrate the main structure of DECAS model, we have provided a schematic diagram and the CRC natural history parameters in the Supplementary Figure S1 ; Supplementary Table S1 .…”
Section: Methodsmentioning
confidence: 99%
“…Given the nature of the DECAS model, which utilizes 1,000 sets of posterior parameters from Bayesian calibration in each simulation, probabilistic sensitivity analyses (PSA) are inherently included in the outputs. This applied to the CRC natural history parameters which were calibrated ( 19 ). To complete the PSA, ranges were specified for the remaining model inputs (such as test characteristics, complication rates, treatment costs, and utility values), and 1,000 random numbers were drawn from a uniform distribution within each range.…”
Section: Methodsmentioning
confidence: 99%