Optimizing the Finnish colorectal cancer population screening program with decision programming

In Finland, colorectal cancer (CRC) incidence rates have steadily increased over the last decades and as of 2020, CRC is the second most common cancer in both males and females. CRC is a crucial concern for the public health of Finland, highlighted by the recent implementation of a national population screening program. In this paper, we optimize the screening test positivity cut-off levels and the use of potential incentives for stratified populations to minimize cancer prevalence. The optimization results, computed with the novel Decision Programming approach for discrete multi-stage decision problems under uncertainty, show the optimal cut-off levels and uses of incentives for Finnish target groups subject to different constraints on colonoscopy capacity. The outcomes of these optimal strategies are estimated to determine the expected corresponding prevalences of CRC and required colonoscopies, and expected third-party costs. Finally, measures describing different equality perspectives are presented. • We develop a model to optimize strategies for two-stage colorectal cancer screening. • The model accounts for different cutoffs for first-stage tests based on age and sex. • Optimal strategies under colonoscopy constraints are found by Decision Programming. • Identified Pareto-optimal strategies minimize cancer prevalence and colonoscopies. • The results offer insights into improving the Finnish cancer screening program.