Jessica Chubak1, Rebecca A Hubbard2, Eric Johnson3, Aruna Kamineni3, Carolyn M Rutter4. 1. Group Health Research Institute, Seattle, WA Department of Epidemiology, University of Washington, Seattle, WA chubak.j@ghc.org. 2. Group Health Research Institute, Seattle, WA Department of Biostatistics, University of Washington, Seattle, WA. 3. Group Health Research Institute, Seattle, WA. 4. Group Health Research Institute, Seattle, WA Department of Biostatistics, University of Washington, Seattle, WA Department of Health Services, University of Washington, Seattle, WA.
Abstract
OBJECTIVES: Analysis of cancer screening effectiveness is challenging in part because of competing tests, which are additional screening tests that identify the condition of interest. For example, studies investigating screening with faecal occult blood tests to prevent colorectal cancer mortality need to consider the occurrence of screening colonoscopy. This paper compares analytic approaches to accounting for competing tests in analyses of cancer screening data. METHODS: We used simulations to compare bias and efficiency across approaches in different scenarios, quantify bias, and make recommendations for analyzing the effectiveness of a screening test in the presence of competing tests. RESULTS: Under all scenarios, the best performing approach for accommodating competing screening tests was censoring at the time of the competing screening test (range in bias across scenarios: -7.6% to 1.6%). Bias from other approaches ranged from 23.9% to 652.1%. CONCLUSIONS: Censoring at the competing screening exam is the recommended approach for studying cancer screening effectiveness in the presence of competing tests. Censoring avoids confounding by prior competing test results and selection bias resulting from analyzing data on participants after they received a competing screening exam. Results from this study are broadly applicable to screening studies for other conditions, including other types of cancer.
OBJECTIVES: Analysis of cancer screening effectiveness is challenging in part because of competing tests, which are additional screening tests that identify the condition of interest. For example, studies investigating screening with faecal occult blood tests to prevent colorectal cancer mortality need to consider the occurrence of screening colonoscopy. This paper compares analytic approaches to accounting for competing tests in analyses of cancer screening data. METHODS: We used simulations to compare bias and efficiency across approaches in different scenarios, quantify bias, and make recommendations for analyzing the effectiveness of a screening test in the presence of competing tests. RESULTS: Under all scenarios, the best performing approach for accommodating competing screening tests was censoring at the time of the competing screening test (range in bias across scenarios: -7.6% to 1.6%). Bias from other approaches ranged from 23.9% to 652.1%. CONCLUSIONS: Censoring at the competing screening exam is the recommended approach for studying cancer screening effectiveness in the presence of competing tests. Censoring avoids confounding by prior competing test results and selection bias resulting from analyzing data on participants after they received a competing screening exam. Results from this study are broadly applicable to screening studies for other conditions, including other types of cancer.
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