Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2026
A Quantitative Framework to Assess the Potential of Earlier Cancer Detection to Improve Cancer Survival.
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Yu Menggang, Tyson Christopher, Limburg Paul J, Beer Tomasz M
Аннотация
BACKGROUND: Earlier cancer detection through advancements in screening technologies and increased screening access and adherence may improve cancer survival. We developed a quantitative approach using a matrix equation to characterize cancer stage shift resulting from cancer screening interventions and estimated resulting survival improvements.
METHODS: The expected percent survival improvement was defined a priori as 20%, and the analysis sought to characterize the stage shift required to achieve this goal. The matrix equation was populated with incidence and cause-specific survival for 16 cancers by stage at diagnosis using the National Cancer Institute Surveillance, Epidemiology, and End Results database. Linear programming was used to solve for the matrix given a set of constraints formulated to steer the solution toward the least amount of downstaging required to achieve the objective and to partially compensate for length-time bias.
RESULTS: Three common trends emerged across almost all cancer types: (i) Most of the survival improvement can be achieved by detecting disease prior to stage IV; (ii) remaining survival improvements can be achieved by detecting just one stage earlier; and (iii) stage I diagnosis is not necessary to achieve measurable survival improvement goals. Lung cancer required more aggressive earlier detection than others, an expected result as lung cancer has a very high incidence and very poor survival.
CONCLUSIONS: This flexible mathematical framework may be helpful for public health officials to characterize how earlier cancer detection can affect cancer survival.
IMPACT: Our results suggest that detecting cancer prior to distant metastases may significantly improve survival.
METHODS: The expected percent survival improvement was defined a priori as 20%, and the analysis sought to characterize the stage shift required to achieve this goal. The matrix equation was populated with incidence and cause-specific survival for 16 cancers by stage at diagnosis using the National Cancer Institute Surveillance, Epidemiology, and End Results database. Linear programming was used to solve for the matrix given a set of constraints formulated to steer the solution toward the least amount of downstaging required to achieve the objective and to partially compensate for length-time bias.
RESULTS: Three common trends emerged across almost all cancer types: (i) Most of the survival improvement can be achieved by detecting disease prior to stage IV; (ii) remaining survival improvements can be achieved by detecting just one stage earlier; and (iii) stage I diagnosis is not necessary to achieve measurable survival improvement goals. Lung cancer required more aggressive earlier detection than others, an expected result as lung cancer has a very high incidence and very poor survival.
CONCLUSIONS: This flexible mathematical framework may be helpful for public health officials to characterize how earlier cancer detection can affect cancer survival.
IMPACT: Our results suggest that detecting cancer prior to distant metastases may significantly improve survival.