OBJECTIVES: Economic evaluation of colorectal cancer screening is challenging because modeling requires accounting for several parameters that are not directly observable. The objective of this article is to describe the available Markov models and to critically analyze their main structural assumptions. METHODS: A systematic search was performed in eight relevant databases (Medline, Embase, Econlit, NHS EED, HEED, HTA, CEA, and EURONHEED), identifying 35 studies that met the inclusion criteria. A comparative analysis of model structure and parameterization was led using two checklists and guidelines for cost effectiveness screening models. RESULTS: Two modeling techniques were identified. One strategy utilized a Markov model to reproduce the natural history of disease and an overlaying model that reproduced the screening process, while the other used a single model to represent a screening program. The majority of studies included only adenoma-carcinoma sequences, while a few also included de novo cancer pathways. Parameterization of adenoma dwell time, sojourn time and surveillance differed between studies, with few of them including time dependent transition probabilities. There was a lack of validation and statistical calibration against local epidemiological data. Most of the studies analyzed failed to perform an adequate literature review and synthesis of diagnostic accuracy properties of the screening tests modeled. Structural uncertainty wasn't analized in any of these studies. CONCLUSIONS: Several strategies to model colorectal cancer screening have been developed, but many challenges remain to adequately represent the natural history of the disease and the screening process. Structural uncertainty analysis and estimation of intermediat outputs could be a useful strategy for understanding the impact of the assumptions of different models on cost effectiveness results.