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Exact Probability Distribution for the ROC Area under Curve
SIMPLE SUMMARY: This contribution allows for the computation of exact p-values and for conducting accurate statistical hypothesis tests of ROC AUC-values. As a result, the development of diagnostic tests is facilitated. This work is illustrated via simulated data and through the development of prote...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10046879/ https://www.ncbi.nlm.nih.gov/pubmed/36980674 http://dx.doi.org/10.3390/cancers15061788 |
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author | Ekström, Joakim Åkerrén Ögren, Jim Sjöblom, Tobias |
author_facet | Ekström, Joakim Åkerrén Ögren, Jim Sjöblom, Tobias |
author_sort | Ekström, Joakim |
collection | PubMed |
description | SIMPLE SUMMARY: This contribution allows for the computation of exact p-values and for conducting accurate statistical hypothesis tests of ROC AUC-values. As a result, the development of diagnostic tests is facilitated. This work is illustrated via simulated data and through the development of proteomic blood biomarkers for the early detection of cancer. ABSTRACT: The Receiver Operating Characteristic (ROC) is a de facto standard for determining the accuracy of in vitro diagnostic (IVD) medical devices, and thus the exactness in its probability distribution is crucial toward accurate statistical inference. We show the exact probability distribution of the ROC AUC-value, hence exact critical values and p-values are readily obtained. Because the exact calculations are computationally intense, we demonstrate a method of geometric interpolation, which is exact in a special case but generally an approximation, vastly increasing computational speeds. The method is illustrated through open access data, demonstrating superiority of 26 composite biomarkers relative to a predicate device. Especially under correction for testing of multiple hypotheses, traditional asymptotic approximations are encumbered by considerable imprecision, adversely affecting IVD device development. The ability to obtain exact p-values will allow more efficient IVD device development. |
format | Online Article Text |
id | pubmed-10046879 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-100468792023-03-29 Exact Probability Distribution for the ROC Area under Curve Ekström, Joakim Åkerrén Ögren, Jim Sjöblom, Tobias Cancers (Basel) Article SIMPLE SUMMARY: This contribution allows for the computation of exact p-values and for conducting accurate statistical hypothesis tests of ROC AUC-values. As a result, the development of diagnostic tests is facilitated. This work is illustrated via simulated data and through the development of proteomic blood biomarkers for the early detection of cancer. ABSTRACT: The Receiver Operating Characteristic (ROC) is a de facto standard for determining the accuracy of in vitro diagnostic (IVD) medical devices, and thus the exactness in its probability distribution is crucial toward accurate statistical inference. We show the exact probability distribution of the ROC AUC-value, hence exact critical values and p-values are readily obtained. Because the exact calculations are computationally intense, we demonstrate a method of geometric interpolation, which is exact in a special case but generally an approximation, vastly increasing computational speeds. The method is illustrated through open access data, demonstrating superiority of 26 composite biomarkers relative to a predicate device. Especially under correction for testing of multiple hypotheses, traditional asymptotic approximations are encumbered by considerable imprecision, adversely affecting IVD device development. The ability to obtain exact p-values will allow more efficient IVD device development. MDPI 2023-03-15 /pmc/articles/PMC10046879/ /pubmed/36980674 http://dx.doi.org/10.3390/cancers15061788 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Ekström, Joakim Åkerrén Ögren, Jim Sjöblom, Tobias Exact Probability Distribution for the ROC Area under Curve |
title | Exact Probability Distribution for the ROC Area under Curve |
title_full | Exact Probability Distribution for the ROC Area under Curve |
title_fullStr | Exact Probability Distribution for the ROC Area under Curve |
title_full_unstemmed | Exact Probability Distribution for the ROC Area under Curve |
title_short | Exact Probability Distribution for the ROC Area under Curve |
title_sort | exact probability distribution for the roc area under curve |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10046879/ https://www.ncbi.nlm.nih.gov/pubmed/36980674 http://dx.doi.org/10.3390/cancers15061788 |
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