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Projecting Benefits and Harms of Novel Cancer Screening Biomarkers: A Study of PCA3 and Prostate Cancer

*Jeanette K Birnbaum, University of Washington 
Ruth Etzioni, Fred Hutchinson Cancer Research Center 
Jing Fan, Fred Hutchinson Cancer Research Center 
Ziding Feng, Fred Hutchinson Cancer Research Center 
Roman Gulati, Fred Hutchinson Cancer Research Center 

Keywords: simulation modeling, screening, biomarkers, early detection policy, prostate cancer

Background: New biomarkers for early detection of cancer must pass through several phases of development to determine their population impact. Simulation modeling can provide early projections of population benefits and harms of a new biomarker given its diagnostic properties. Prostate cancer antigen 3 (PCA3) is a promising prostate cancer biomarker still in early stages of development. We use simulation modeling to evaluate the impact of adding PCA3 to prostate-specific antigen (PSA) screening on prostate cancer detection and survival in the United States.

Methods: We used data from a recent study of PCA3 distributions in men referred for prostate biopsy to add PCA3 to an existing simulation model of PSA and disease progression. We specified several PSA-PCA3 strategies designed to improve specificity and reduce overdiagnosis. Using these strategies to screen a cohort of men biennially between ages 50 and 74, we projected true and false positive tests, overdiagnoses, and lives saved relative to a PSA-based strategy with a cutoff of 4.0 ng/ml for biopsy referral.

Results: Strategies that combined PCA3 with PSA significantly reduced false positive tests and overdiagnosis compared to PSA>4.0 ng/ml, but also reduced lives saved. Using PCA3>35 for biopsy referral in men with PSA between 4.0 and 10.0 ng/ml retained 85% of lives saved while approximately halving false positives and reducing overdiagnoses by 25%.

Conclusions: Adding PCA3 to PSA screening can significantly reduce adverse screening outcomes. Strategies can be identified that preserve most of the lives saved relative to PSA-based screening. Simulation modeling allows us to project population outcomes of new screening biomarkers and may help inform early detection policy.