Modeled reductions in late-stage cancer with a multi-cancer early detection test

Abstract

Background: Cancer is the second leading cause of death globally, with many cases detected at a late stage when prognosis is poor. New technologies enabling multi-cancer early detection (MCED) may make "universal cancer screening" possible. We extend single-cancer models to understand the potential public health effects of adding a MCED test to usual care Methods: We obtained data on stage-specific incidence and survival of all invasive cancers diagnosed in persons aged 50-79 between 2006 and 2015 from the US Surveillance, Epidemiology, and End Results (SEER) program, and combined this with published performance of a MCED test in a state transition model (interception model) to predict diagnostic yield, stage shift, and potential mortality reductions. We model long-term (incident) performance, accounting for constraints on detection due to repeated screening Results: The MCED test could intercept 485 cancers per year per 100,000 persons, reducing late-stage (III+IV) incidence by 78% in those intercepted. Accounting for lead time, this could reduce 5-year cancer mortality by 39% in those intercepted, resulting in an absolute reduction of 104 deaths per 100,000, or 26% of all cancer deaths. Findings are robust across tumor growth scenarios Conclusions: Evaluating the impact of a MCED test that affects multiple cancer types simultaneously requires modeling across all cancer incidence. Assuming MCED test metrics hold in a clinical setting, the aggregate potential to improve public health is significant Impact: Modeling performance of a MCED test in a representative population suggests that it could substantially reduce overall cancer mortality if added to usual care