Bias due to coarsening of time intervals in the inference for the effectiveness of colorectal cancer screening

Author:

Karmakar Bikram1ORCID,Zauber Ann G2,Hahn Anne I2,Lau Yan Kwan3ORCID,Doubeni Chyke A4,Joffe Marshall M5

Affiliation:

1. Department of Statistics, College of Liberal Arts and Sciences, University of Florida , Gainesville, FL, USA

2. Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center , New York, NY, USA

3. Department of Epidemiology, School of Public Health, University of Michigan , Ann Arbor, MI, USA

4. Family and Community Medicine, Arthur G. James Cancer Hospital and Solove Research Institute , Columbus, OH, USA

5. Department of Biostatistics and Epidemiology, Center for Clinical Epidemiology and Biostatistics, The University of Pennsylvania School of Medicine , Philadelphia, PA, USA

Abstract

Abstract Background Observational studies are frequently used to estimate the comparative effectiveness of different colorectal cancer (CRC) screening methods due to the practical limitations and time needed to conduct large clinical trials. However, time-varying confounders, e.g. polyp detection in the last screening, can bias statistical results. Recently, generalized methods, or G-methods, have been used for the analysis of observational studies of CRC screening, given their ability to account for such time-varying confounders. Discretization, or the process of converting continuous functions into discrete counterparts, is required for G-methods when the treatment and outcomes are assessed at a continuous scale. Development This paper evaluates the interplay between time-varying confounding and discretization, which can induce bias in assessing screening effectiveness. We investigate this bias in evaluating the effect of different CRC screening methods that differ from each other in typical screening frequency. Application First, using theory, we establish the direction of the bias. Then, we use simulations of hypothetical settings to study the bias magnitude for varying levels of discretization, frequency of screening and length of the study period. We develop a method to assess possible bias due to coarsening in simulated situations. Conclusions The proposed method can inform future studies of screening effectiveness, especially for CRC, by determining the choice of interval lengths where data are discretized to minimize bias due to coarsening while balancing computational costs.

Funder

National Institutes of Health

Publisher

Oxford University Press (OUP)

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