Estimating the incremental population health impact of a multi-cancer early detection (MCED) test to complement existing screening among elevated risk populations with multiple cancer risk factors: a mathematical modeling study - Ashley Kim; Ze Cong; Abdul-Rahman Jazieh; Timothy R. Church; Heidi Reichert; Gina Nicholson; Jon Fryzek; Sarah S. Cohen (BMC Health Services Research)
Abstract Background The added benefits of a multi-cancer early detection (MCED) test among individuals with multiple risk factors will help policy decision-makers allocate limited healthcare resources. This study sought to estimate the population health implications of adding an MCED test to standard-of-care (SOC) cancer screening tests among individuals aged 50–79 years with additional cancer risk factors (i.e., tobacco use, family history of cancer, and/or obesity). Methods A mathematical model was developed to assess the potential screening efficiency of an MCED test in addition to current guideline-recommended screenings. Among the US population of 107 million adults aged 50–79 years, the size of, and cancer risk among specific subgroups (i.e., smokers, obese individuals, those with a family history of cancer) as well as the general population were estimated from the literature. Published estimates of screening uptake and/or performance were used to model the number of cancers detected by SOC screening alone, and the number of incremental cancers that could be detected by an MCED test. Screening efficiency outcomes included the true-positive:false-positive (TP:FP) ratio, diagnostic yield (DY), and cancer detection rate (CDR). Sensitivity analyses were conducted by varying the values of key parameters. Results Among all subgroups, the TP:FP ratios were higher with an MCED test than with SOC screening alone, and higher than in the general population, suggesting improved screening efficiency with an MCED test. The estimated TP:FP ratios were 1:43.3 (SOC)/1:1.1 (MCED), 1:40.4/1:0.8, 1:36.9/1:0.5 among former, ever, and current smokers, respectively, 1:38.3/1:0.9 (those with a family history of cancer), and 1:39.3/1:1.1 (obese individuals). Among the general population, the TP:FP ratios were 1:43.5/1:1.1. Across all subpopulations, the DY and CDR increased by up to threefold with an MCED test, when compared to SOC screening alone, with up to 75% of cancers detected with an MCED test lacking a screening paradigm. These results were robust in sensitivity analyses. Conclusions Adding an MCED test could improve screening efficiency among individuals with multiple risk factors, as well as the general population.