Temporal bias in case-control design: preventing reliable predictions of the future

Author:

Yuan William,Beaulieu-Jones Brett K.ORCID,Yu Kun-HsingORCID,Lipnick Scott L.,Palmer NathanORCID,Loscalzo JosephORCID,Cai Tianxi,Kohane Isaac S.

Abstract

AbstractOne of the primary tools that researchers use to predict risk is the case-control study. We identify a flaw, temporal bias, that is specific to and uniquely associated with these studies that occurs when the study period is not representative of the data that clinicians have during the diagnostic process. Temporal bias acts to undermine the validity of predictions by over-emphasizing features close to the outcome of interest. We examine the impact of temporal bias across the medical literature, and highlight examples of exaggerated effect sizes, false-negative predictions, and replication failure. Given the ubiquity and practical advantages of case-control studies, we discuss strategies for estimating the influence of and preventing temporal bias where it exists.

Funder

NVIDIA Graduate Fellowship AWS Cloud Credits for Research NVIDIA GPU Grant

Publisher

Springer Science and Business Media LLC

Subject

General Physics and Astronomy,General Biochemistry, Genetics and Molecular Biology,General Chemistry

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