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Objective To assess the range of strategies analysed in European cost-effectiveness analyses (CEAs) of colorectal cancer (CRC) screening with respect to the screening intervals, age ranges and test cut-offs used to define positivity, to examine how this might influence what strategies are found to be optimal, and compare them with the current screening policies with a focus on the screening interval. Methods We searched PubMed, Web of Science and Scopus for peer-reviewed, model-based CEAs of CRC screening. We included studies on average-risk European populations using the guaiac faecal occult blood test (gFOBT) or faecal immunochemical test (FIT). We adapted Drummond’s ten-point checklist to appraise study quality. Results We included 39 studies that met the inclusion criteria. Biennial screening was the most frequently used interval which was analysed in 37 studies. Annual screening was assessed in 13 studies, all of which found it optimally cost-effective. Despite this, 25 of 26 European stool-based programmes use biennial screening. Many CEAs did not vary the age range, but the 14 that did generally found broader ranges optimal. Only 11 studies considered alternative FIT cut-offs, 9 of which found lower cut-offs superior. Conflicts between current policy and CEA evidence are less clear regarding age ranges and cut-offs. Conclusions The existing CEA evidence indicates that the widely adopted biennial frequency of stool-based testing in Europe is suboptimal. It is likely that many more lives could be saved throughout Europe if programmes could be offered with more intensive annual screening. Supplementary Information The online version contains supplementary material available at 10.1007/s40258-023-00819-3.

Applied cost-effectiveness analysis models are an important tool for assessing health and economic effects of healthcare interventions but are not best suited for illustrating methods. Our objective is to provide a simple, open-source model for the simulation of disease-screening cost-effectiveness for teaching and research purposes. We introduce our model and provide an initial application to examine changes to the efficiency frontier as input parameters vary and to demonstrate face validity. We described a vectorised, discrete-event simulation of screening in R with an Excel interface to define parameters and inspect principal results. An R Shiny app permits dynamic interpretation of simulation outputs. An example with 8161 screening strategies illustrates the cost and effectiveness of varying the disease sojourn time, treatment effectiveness, and test performance characteristics and costs on screening policies. Many of our findings are intuitive and straightforward, such as a reduction in screening costs leading to decreased overall costs and improved cost-effectiveness. Others are less obvious and depend on whether we consider gross outcomes or those net to no screening. For instance, enhanced treatment of symptomatic disease increases gross effectiveness, but reduces the net effectiveness and cost-effectiveness of screening. A lengthening of the preclinical sojourn time has ambiguous effects relative to no screening, as cost-effectiveness improves for some strategies but deteriorates for others. Our simple model offers an accessible platform for methods research and teaching. We hope it will serve as a public good and promote an intuitive understanding of the cost-effectiveness of screening.

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