  Multi-cancer early detection (MCED) tests offer to screen for multiple types
of cancer with a single blood sample. Despite their promising diagnostic
performance, evidence regarding their population benefit is not yet available.
Expecting that benefit will derive from detecting cancer before it progresses
to an advanced stage, we develop a general two-stage model to project the
reduction in advanced-stage diagnoses given stage-specific test sensitivities
and testing ages. The model can be estimated using cancer registry data and
values for the mean overall and advanced-stage preclinical sojourn times. We
first estimate the model for lung cancer and validate it against the stage
shift observed in the National Lung Screening Trial. We then estimate the model
for liver, pancreas, and bladder cancer, which have no recommended screening
tests, and we project stage shifts under a shared MCED testing protocol. Our
framework transparently integrates available data to project reductions in
advanced-stage diagnoses due to MCED testing.
