10559965epi141224-sup-140239_1_art_file_2796496_ngzx3g.doc (38 kB)
Supplementary Table 1 from Projecting Benefits and Harms of Novel Cancer Screening Biomarkers: A Study of PCA3 and Prostate Cancer
journal contributionposted on 2023-03-31, 13:44 authored by Jeanette K. Birnbaum, Ziding Feng, Roman Gulati, Jing Fan, Yair Lotan, John T. Wei, Ruth Etzioni
Supplementary Table 1 - Data and assumptions used to construct each element of the natural history model of prostate cancer and the extension incorporating PCA3.
ARTICLE ABSTRACTBackground: New biomarkers for early detection of cancer must pass through several phases of development. Early phases provide information on diagnostic properties but not on population benefits and harms. Prostate cancer antigen 3 (PCA3) is a promising prostate cancer biomarker still in early development. We use simulation modeling to project the impact of adding PCA3 to prostate-specific antigen (PSA) screening on prostate cancer detection and mortality in the United States.Methods: We used data from a recent study of PCA3 in men referred for prostate biopsy to extend an existing simulation model of PSA growth, disease progression, and survival. 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: We identified several PSA-PCA3 strategies that substantially reduced false-positive tests and overdiagnoses while preserving the majority of lives saved. 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.Impact: Simulation modeling provides advance projections of population outcomes of new screening biomarkers and may help guide early detection research. Cancer Epidemiol Biomarkers Prev; 24(4); 677–82. ©2015 AACR.