OBJECTIVES:

Even with current screening technologies, cancer remains a leading cause of death worldwide. More than 20 MCED tests are currently in development. Even for highly sensitive and specific assays, suboptimal adherence will impact the effectiveness of MCED tests. This study used an analytical model to determine the effect of adherence on the effectiveness of MCED screening programs, using lung cancer to illustrate our findings.

METHODS:

We constructed a generalized, cancer-agnostic, state transition model in R, based on the work of Hubbell et. al., to estimate the benefits of an MCED screening program compared to existing standard of care. Our generalized model predicts the shift in stage at diagnosis given MCED test characteristics, diagnostic pathway, incidence rates, dwell times, survival, and screening adherence. Primary outcomes are stage at diagnosis shift and increase in survival. The model extends existing interception models by accounting for adherence.

RESULTS:

We modeled a hypothetical cohort of 100,000 persons aged 50 to 79 eligible for lung cancer screening and a test with 21.9%, 79.5%, 90.7%, and 95.2% sensitivity at stages I, to IV. Under 100% adherence, the model is estimated to shift 56% of Stage III and IV cancers to Stage I or II, resulting in 49.6 fewer advanced stage tumors. At adherence rates of 75%, 50%, and 25%, the shift in late-stage to early-stage cancer falls to 43%, 29%, and 14% respectively, deaths at 5-years are reduced by 23% to 6%.

CONCLUSIONS:

Emerging MCED tests are a paradigm shift in cancer screening, but the effectiveness of MCED testing is significantly impacted by adherence. In the case of lung cancer, we find that adherence to annual screening has a large impact on overall effectiveness. Accounting for patient adherence to screening improves estimates of value, reflecting the real world use of these novel tests.