Determination of cutoff values for biomarkers in clinical studies

In clinical and epidemiological studies, biomarkers are associated with disease diagnosis and prognosis. Using biomarkers to classify subjects into groups, such as high-risk or low-risk, may help with the application of the most appropriate care or procedure within each group. In the case of a conti...

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Main Authors: Sook Young Woo, Seonwoo Kim
Format: Article
Language:English
Published: Sungkyunkwan University School of Medi 2020-03-01
Series:Precision and Future Medicine
Subjects:
Online Access:http://www.pfmjournal.org/upload/pdf/pfm-2019-00135.pdf
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author Sook Young Woo
Seonwoo Kim
author_facet Sook Young Woo
Seonwoo Kim
author_sort Sook Young Woo
collection DOAJ
description In clinical and epidemiological studies, biomarkers are associated with disease diagnosis and prognosis. Using biomarkers to classify subjects into groups, such as high-risk or low-risk, may help with the application of the most appropriate care or procedure within each group. In the case of a continuous biomarker, a cutoff value to define the groups should be determined. A widespread and straightforward method is to select a cutoff value that minimizes the P-value when comparing the outcomes between the two groups. However, a problem that arises with this procedure is that of multiple testing, which leads to an increase in false positive error rate, and thus the significance of the obtained cutoff value tends to be overestimated. In this article, we introduce several methods to correct the P-value for determining the statistical significance of an optimal cutoff value for a quantitatively measured biomarker with applications to clinical data.
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spelling doaj.art-6ce91edb9aea458cb8239ba06c8562e62022-12-22T03:50:43ZengSungkyunkwan University School of MediPrecision and Future Medicine2508-79402508-79592020-03-01412810.23838/pfm.2019.0013567Determination of cutoff values for biomarkers in clinical studiesSook Young Woo0Seonwoo Kim Statistics and Data Center, Samsung Medical Center, Seoul, KoreaIn clinical and epidemiological studies, biomarkers are associated with disease diagnosis and prognosis. Using biomarkers to classify subjects into groups, such as high-risk or low-risk, may help with the application of the most appropriate care or procedure within each group. In the case of a continuous biomarker, a cutoff value to define the groups should be determined. A widespread and straightforward method is to select a cutoff value that minimizes the P-value when comparing the outcomes between the two groups. However, a problem that arises with this procedure is that of multiple testing, which leads to an increase in false positive error rate, and thus the significance of the obtained cutoff value tends to be overestimated. In this article, we introduce several methods to correct the P-value for determining the statistical significance of an optimal cutoff value for a quantitatively measured biomarker with applications to clinical data.http://www.pfmjournal.org/upload/pdf/pfm-2019-00135.pdfbiomarkerscorrected p-valuecutofffalse positive error
spellingShingle Sook Young Woo
Seonwoo Kim
Determination of cutoff values for biomarkers in clinical studies
Precision and Future Medicine
biomarkers
corrected p-value
cutoff
false positive error
title Determination of cutoff values for biomarkers in clinical studies
title_full Determination of cutoff values for biomarkers in clinical studies
title_fullStr Determination of cutoff values for biomarkers in clinical studies
title_full_unstemmed Determination of cutoff values for biomarkers in clinical studies
title_short Determination of cutoff values for biomarkers in clinical studies
title_sort determination of cutoff values for biomarkers in clinical studies
topic biomarkers
corrected p-value
cutoff
false positive error
url http://www.pfmjournal.org/upload/pdf/pfm-2019-00135.pdf
work_keys_str_mv AT sookyoungwoo determinationofcutoffvaluesforbiomarkersinclinicalstudies
AT seonwookim determinationofcutoffvaluesforbiomarkersinclinicalstudies