Can Multi-Cancer Early Detection Tests Reduce Cancer Mortality?
Author(s)
Jade Xiao, PhD1, Andrew ElHabr, PhD1, Christopher Tyson, PhD2, Xiting Cao, PhD2, Sana Raoof, MD, PhD3, A Mark Fendrick, MD4, Burak Ozbay, PhD2, Paul Limburg, MD2, Tomasz M. Beer, MD2, Ashish A. Deshmukh, PhD5, Andrew Briggs, DPhil6, Jag Chhatwal, PhD7.
1Value Analytics Labs, Boston, MA, USA, 2Exact Sciences Corporation, Madison, WI, USA, 3Memorial Sloan Kettering Cancer Center, New York, NY, USA, 4School of Public Health, University of Michigan, Ann Arbor, MI, USA, 5Medical University of South Carolina, Charleston, SC, USA, 6London School of Hygiene & Tropical Medicine, London, United Kingdom, 7Massachusetts General Hospital, Boston, MA, USA.
1Value Analytics Labs, Boston, MA, USA, 2Exact Sciences Corporation, Madison, WI, USA, 3Memorial Sloan Kettering Cancer Center, New York, NY, USA, 4School of Public Health, University of Michigan, Ann Arbor, MI, USA, 5Medical University of South Carolina, Charleston, SC, USA, 6London School of Hygiene & Tropical Medicine, London, United Kingdom, 7Massachusetts General Hospital, Boston, MA, USA.
OBJECTIVES: Emerging liquid biopsy multi-cancer early detection (MCED) tests have the potential to revolutionize early cancer detection. Using a simulation model, we estimated their impact on cancer mortality considering different levels of MCED uptake and adherence.
METHODS: We developed Simulation Model for MCED (SiMCED), a continuous-time, discrete-event microsimulation model of 14 solid tumor cancers. Cancer type- and stage-specific MCED test sensitivities were derived from a large, multi-center, prospectively collected, retrospective case-control study (ASCEND-2). The model was calibrated to reproduce annual incidence rates of diagnosis as captured in the Surveillance, Epidemiology, and End Results (SEER) database, while accounting for the unobserved cancer burden. Using a 10-year time horizon, we simulated the life course of 5 million US adults aged 50-84 years. Cancer diagnosis could arise from usual care or MCED screening. After a cancer diagnosis, individuals followed SEER survival curves to determine the time and cause of death (cancer- or non-cancer-related). Additionally, scenario analysis was performed to evaluate mortality reduction with decreased levels of MCED uptake (the proportion of the population who will take MCED when offered) and adherence (the probability of an individual accepting MCED each time it is offered).
RESULTS: Compared to usual care only, the supplemental use of MCED screening reduced cancer mortality by 18% (2,612 versus 2,149 per 100,000), assuming perfect MCED uptake and adherence. In the scenario analysis, 10-year mortality reduction was 13% (2,612 versus 2,282 per 100,000) with 100% uptake and 70% adherence; 12% (2,612 versus 2,293 per 100,000) with 70% uptake and 100% adherence; and 9% (2,612 versus 2,385 per 100,000) with 70% uptake and 70% adherence.
CONCLUSIONS: Our study suggests that MCED screening could be effective for reducing cancer mortality. Even when uptake and adherence were more modest, MCED screening still conferred meaningful mortality benefits.
METHODS: We developed Simulation Model for MCED (SiMCED), a continuous-time, discrete-event microsimulation model of 14 solid tumor cancers. Cancer type- and stage-specific MCED test sensitivities were derived from a large, multi-center, prospectively collected, retrospective case-control study (ASCEND-2). The model was calibrated to reproduce annual incidence rates of diagnosis as captured in the Surveillance, Epidemiology, and End Results (SEER) database, while accounting for the unobserved cancer burden. Using a 10-year time horizon, we simulated the life course of 5 million US adults aged 50-84 years. Cancer diagnosis could arise from usual care or MCED screening. After a cancer diagnosis, individuals followed SEER survival curves to determine the time and cause of death (cancer- or non-cancer-related). Additionally, scenario analysis was performed to evaluate mortality reduction with decreased levels of MCED uptake (the proportion of the population who will take MCED when offered) and adherence (the probability of an individual accepting MCED each time it is offered).
RESULTS: Compared to usual care only, the supplemental use of MCED screening reduced cancer mortality by 18% (2,612 versus 2,149 per 100,000), assuming perfect MCED uptake and adherence. In the scenario analysis, 10-year mortality reduction was 13% (2,612 versus 2,282 per 100,000) with 100% uptake and 70% adherence; 12% (2,612 versus 2,293 per 100,000) with 70% uptake and 100% adherence; and 9% (2,612 versus 2,385 per 100,000) with 70% uptake and 70% adherence.
CONCLUSIONS: Our study suggests that MCED screening could be effective for reducing cancer mortality. Even when uptake and adherence were more modest, MCED screening still conferred meaningful mortality benefits.
Conference/Value in Health Info
2025-05, ISPOR 2025, Montréal, Quebec, CA
Value in Health, Volume 28, Issue S1
Code
MSR112
Topic
Methodological & Statistical Research
Disease
SDC: Oncology