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...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Sungkyunkwan University School of Medi
2020-03-01
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| Series: | Precision and Future Medicine |
| Subjects: | |
| Online Access: | http://www.pfmjournal.org/upload/pdf/pfm-2019-00135.pdf |
| Summary: | 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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| ISSN: | 2508-7940 2508-7959 |