Projecting the impact of multicancer early detection tests on stage at diagnosis: a modeling approach
Principal Investigator
Name
JANE LANGE
Degrees
Ph.D.
Institution
OREGON HEALTH AND SCIENCES UNIVERSITY
Position Title
Staff Scientist
Email
About this CDAS Project
Study
NLST
(Learn more about this study)
Project ID
NLST-1012
Initial CDAS Request Approval
Jan 30, 2023
Title
Projecting the impact of multicancer early detection tests on stage at diagnosis: a modeling approach
Summary
Multi Cancer screening tests offer the promise of detecting multiple types of cancer with a single
blood sample. At least one test is now widely available, with several others in the pipeline. However, the
promise of these tests is tempered by a lack of knowledge of their benefit and harms in the population.
In absence of a rigorous clinical trial, modeling has the potential to provide clues about multicancer
tests’ impact on population mortality. The mortality benefit of screening is broadly conceptualized as
occurring through a reduction in advance stage disease at diagnosis. We develop a general framework for
projecting the reduction in advanced stage disease for a given cancer site with known mean sojourn time
based on a screening test with a given sensitivity. We evaluate the performance of the model on the
National Lung Screen trial and discuss its limitations and potential extensions.
blood sample. At least one test is now widely available, with several others in the pipeline. However, the
promise of these tests is tempered by a lack of knowledge of their benefit and harms in the population.
In absence of a rigorous clinical trial, modeling has the potential to provide clues about multicancer
tests’ impact on population mortality. The mortality benefit of screening is broadly conceptualized as
occurring through a reduction in advance stage disease at diagnosis. We develop a general framework for
projecting the reduction in advanced stage disease for a given cancer site with known mean sojourn time
based on a screening test with a given sensitivity. We evaluate the performance of the model on the
National Lung Screen trial and discuss its limitations and potential extensions.
Aims
* Develop a model of reduction in advanced stage disease (stage shift) that is applicable to cancer sites without existing screenig
* Validate the model against the observed stage shift in the NLST
-at the end of the trial
-by screen/followup year.
Collaborators
Ruth Etzioni, Kemal Gogebakan
Related Publications
-
Projecting the impact of multi-cancer early detection on late-stage incidence using multi-state disease modeling.
Lange JM, Gogebakan KC, Gulati R, Etzioni R
Cancer Epidemiol Biomarkers Prev. 2024 Mar 20 PUBMED