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Temporal bias in case-control design: preventing reliable predictions of the future
One 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 pr...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7889612/ https://www.ncbi.nlm.nih.gov/pubmed/33597541 http://dx.doi.org/10.1038/s41467-021-21390-2 |
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author | Yuan, William Beaulieu-Jones, Brett K. Yu, Kun-Hsing Lipnick, Scott L. Palmer, Nathan Loscalzo, Joseph Cai, Tianxi Kohane, Isaac S. |
author_facet | Yuan, William Beaulieu-Jones, Brett K. Yu, Kun-Hsing Lipnick, Scott L. Palmer, Nathan Loscalzo, Joseph Cai, Tianxi Kohane, Isaac S. |
author_sort | Yuan, William |
collection | PubMed |
description | One 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. |
format | Online Article Text |
id | pubmed-7889612 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-78896122021-03-03 Temporal bias in case-control design: preventing reliable predictions of the future Yuan, William Beaulieu-Jones, Brett K. Yu, Kun-Hsing Lipnick, Scott L. Palmer, Nathan Loscalzo, Joseph Cai, Tianxi Kohane, Isaac S. Nat Commun Article One 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. Nature Publishing Group UK 2021-02-17 /pmc/articles/PMC7889612/ /pubmed/33597541 http://dx.doi.org/10.1038/s41467-021-21390-2 Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Yuan, William Beaulieu-Jones, Brett K. Yu, Kun-Hsing Lipnick, Scott L. Palmer, Nathan Loscalzo, Joseph Cai, Tianxi Kohane, Isaac S. Temporal bias in case-control design: preventing reliable predictions of the future |
title | Temporal bias in case-control design: preventing reliable predictions of the future |
title_full | Temporal bias in case-control design: preventing reliable predictions of the future |
title_fullStr | Temporal bias in case-control design: preventing reliable predictions of the future |
title_full_unstemmed | Temporal bias in case-control design: preventing reliable predictions of the future |
title_short | Temporal bias in case-control design: preventing reliable predictions of the future |
title_sort | temporal bias in case-control design: preventing reliable predictions of the future |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7889612/ https://www.ncbi.nlm.nih.gov/pubmed/33597541 http://dx.doi.org/10.1038/s41467-021-21390-2 |
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