Tumor localization strategies of multicancer early detection tests: a quantitative assessment.

Abstract

Background: Multicancer early detection tests may expand cancer screening. Characterizing diagnostic resolution approaches following positive multicancer early detection tests is critical. Two trials employed distinct resolution approaches: a molecular signal to predict tissue of origin and an imaging-based diagnostic strategy. This modeling study characterizes diagnostic journeys and impact in a hypothetical population of average-risk multicancer early detection-eligible patients.

Methods: A mathematical expression for diagnostic burden was derived using positive predictive value (PPV), molecular tissue of origin localization accuracy, and numbers of procedures associated with each diagnostic outcome. Imaging-based and molecular tissue of origin-informed strategies were compared. Excess lifetime cancer risk due to futile radiation exposure was estimated using organ-specific diagnostic imaging radiation doses.

Results: Across all PPVs and localization performances, a molecular tissue of origin strategy resulted in a higher diagnostic burden (mean = 3.6 [0.445] procedures vs mean = 2.6 [0.100] procedures) for the imaging strategy. Estimated diagnostic burden was higher for molecular tissue of origin in 95.5% of all PPV and tissue of origin accuracy combinations; at least 79% PPV and 90% accuracy would be required for a molecular tissue of origin-informed strategy to be less burdensome than imaging. The maximum rate of excess cancer incidence from radiation exposure for multicancer early detection false-positive results (individuals aged 50-84 years) was 64.6 of 100 000 (annual testing, 99% specificity), 48.5 of 100 000 (biennial testing, 98.5% specificity), and 64.6 of 100 000 (biennial testing, 98% specificity).

Conclusions: An imaging-based diagnostic strategy is more efficient than a molecular tissue of origin-informed approach across almost all PPV and tissue of origin accuracy combinations. The use of an imaging-based approach for cancer localization can be efficient and low-risk compared with a molecular-informed approach.