Background: There is growing evidence for personalizing colorectal cancer screening based on risk factors. We compared the cost-effectiveness of personalized colorectal cancer screening based on polygenic risk and family history to uniform screening. Methods: Using the MISCAN-Colon model, we simulated a cohort of 100 million 40-year-olds, offering them uniform or personalized screening. Individuals were categorized based on polygenic risk and family history of colorectal cancer. We varied screening strategies by start age, interval and test and estimated costs, and quality-adjusted life years (QALY). In our analysis, we (i) assessed the cost-effectiveness of uniform screening; (ii) developed personalized screening scenarios based on optimal screening strategies by risk group; and (iii) compared the cost-effectiveness of both. Results: At a willingness-to-pay threshold of $50,000/QALY, the optimal uniform screening scenario was annual fecal immunochemical testing (FIT) from ages 50 to 74 years, whereas for personalized screening the optimal screening scenario consisted of annual and biennial FIT screening except for those at highest risk who were offered 5-yearly colonoscopy from age 50 years. Although these scenarios gained the same number of QALYs (17,887), personalized screening was not cost-effective, costing an additional $428,953 due to costs associated with determining risk (assumed to be $240 per person). Personalized screening was cost-effective when these costs were less than ~$48. Conclusions: Uniform colorectal cancer screening currently appears more cost-effective than personalized screening based on polygenic risk and family history. However, cost-effectiveness is highly dependent on the cost of determining risk. Impact: Personalized screening could become increasingly viable as costs for determining risk decrease.
Cenin, D. R., Naber, S. K., de Weerdt, A. C., Jenkins, M. A., Preen, D. B., Ee, H. C., ... Lansdorp-Vogelaar, I. (2020). Cost-effectiveness of personalized screening for colorectal cancer based on polygenic risk and family history. Cancer Epidemiology Biomarkers and Prevention, 29, 10-21. https://doi.org/10.1158/1055-9965.EPI-18-1123