Evaluating the Performances of Biomarkers over a Restricted Domain of High Sensitivity

The burgeoning advances in high-throughput technologies have posed a great challenge to the identification of novel biomarkers for diagnosing, by contemporary models and methods, through bioinformatics-driven analysis. Diagnostic performance metrics such as the partial area under the <inline-form...

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Autores principales:	Manuel Franco, Juana-María Vivo
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	<i>ROC</i> partial area scaled partial area index high sensitivity negative diagnostic likelihood ratio variance of <i>FpAUC</i> biomarker performance Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/ac7ba9ebfd6949f59103c075332c5fa3
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spelling	oai:doaj.org-article:ac7ba9ebfd6949f59103c075332c5fa32021-11-11T18:21:12ZEvaluating the Performances of Biomarkers over a Restricted Domain of High Sensitivity10.3390/math92128262227-7390https://doaj.org/article/ac7ba9ebfd6949f59103c075332c5fa32021-11-01T00:00:00Zhttps://www.mdpi.com/2227-7390/9/21/2826https://doaj.org/toc/2227-7390The burgeoning advances in high-throughput technologies have posed a great challenge to the identification of novel biomarkers for diagnosing, by contemporary models and methods, through bioinformatics-driven analysis. Diagnostic performance metrics such as the partial area under the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>R</mi><mi>O</mi><mi>C</mi></mrow></semantics></math></inline-formula> (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>p</mi><mi>A</mi><mi>U</mi><mi>C</mi></mrow></semantics></math></inline-formula>) indexes exhibit limitations to analysing genomic data. Among other issues, the inability to differentiate between biomarkers whose <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>R</mi><mi>O</mi><mi>C</mi></mrow></semantics></math></inline-formula> curves cross each other with the same <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>p</mi><mi>A</mi><mi>U</mi><mi>C</mi></mrow></semantics></math></inline-formula> value, the inappropriate expression of non-concave <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>R</mi><mi>O</mi><mi>C</mi></mrow></semantics></math></inline-formula> curves, and the lack of a convenient interpretation, restrict their use in practice. Here, we have proposed the fitted partial area index (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>F</mi><mi>p</mi><mi>A</mi><mi>U</mi><mi>C</mi></mrow></semantics></math></inline-formula>), which is computable through an algorithm valid for any <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>R</mi><mi>O</mi><mi>C</mi></mrow></semantics></math></inline-formula> curve shape, as an alternative performance summary for the evaluation of highly sensitive biomarkers. The proposed approach is based on fitter upper and lower bounds of the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>p</mi><mi>A</mi><mi>U</mi><mi>C</mi></mrow></semantics></math></inline-formula> in a high-sensitivity region. Through variance estimates, simulations, and case studies for diagnosing leukaemia, and ovarian and colon cancers, we have proven the usefulness of the proposed metric in terms of restoring the interpretation and improving diagnostic accuracy. It is robust and feasible even when the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>R</mi><mi>O</mi><mi>C</mi></mrow></semantics></math></inline-formula> curve shows hooks, and solves performance ties between competitive biomarkers.Manuel FrancoJuana-María VivoMDPI AGarticle<i>ROC</i> partial areascaled partial area indexhigh sensitivitynegative diagnostic likelihood ratiovariance of <i>FpAUC</i>biomarker performanceMathematicsQA1-939ENMathematics, Vol 9, Iss 2826, p 2826 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	<i>ROC</i> partial area scaled partial area index high sensitivity negative diagnostic likelihood ratio variance of <i>FpAUC</i> biomarker performance Mathematics QA1-939
spellingShingle	<i>ROC</i> partial area scaled partial area index high sensitivity negative diagnostic likelihood ratio variance of <i>FpAUC</i> biomarker performance Mathematics QA1-939 Manuel Franco Juana-María Vivo Evaluating the Performances of Biomarkers over a Restricted Domain of High Sensitivity
description	The burgeoning advances in high-throughput technologies have posed a great challenge to the identification of novel biomarkers for diagnosing, by contemporary models and methods, through bioinformatics-driven analysis. Diagnostic performance metrics such as the partial area under the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>R</mi><mi>O</mi><mi>C</mi></mrow></semantics></math></inline-formula> (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>p</mi><mi>A</mi><mi>U</mi><mi>C</mi></mrow></semantics></math></inline-formula>) indexes exhibit limitations to analysing genomic data. Among other issues, the inability to differentiate between biomarkers whose <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>R</mi><mi>O</mi><mi>C</mi></mrow></semantics></math></inline-formula> curves cross each other with the same <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>p</mi><mi>A</mi><mi>U</mi><mi>C</mi></mrow></semantics></math></inline-formula> value, the inappropriate expression of non-concave <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>R</mi><mi>O</mi><mi>C</mi></mrow></semantics></math></inline-formula> curves, and the lack of a convenient interpretation, restrict their use in practice. Here, we have proposed the fitted partial area index (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>F</mi><mi>p</mi><mi>A</mi><mi>U</mi><mi>C</mi></mrow></semantics></math></inline-formula>), which is computable through an algorithm valid for any <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>R</mi><mi>O</mi><mi>C</mi></mrow></semantics></math></inline-formula> curve shape, as an alternative performance summary for the evaluation of highly sensitive biomarkers. The proposed approach is based on fitter upper and lower bounds of the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>p</mi><mi>A</mi><mi>U</mi><mi>C</mi></mrow></semantics></math></inline-formula> in a high-sensitivity region. Through variance estimates, simulations, and case studies for diagnosing leukaemia, and ovarian and colon cancers, we have proven the usefulness of the proposed metric in terms of restoring the interpretation and improving diagnostic accuracy. It is robust and feasible even when the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>R</mi><mi>O</mi><mi>C</mi></mrow></semantics></math></inline-formula> curve shows hooks, and solves performance ties between competitive biomarkers.
format	article
author	Manuel Franco Juana-María Vivo
author_facet	Manuel Franco Juana-María Vivo
author_sort	Manuel Franco
title	Evaluating the Performances of Biomarkers over a Restricted Domain of High Sensitivity
title_short	Evaluating the Performances of Biomarkers over a Restricted Domain of High Sensitivity
title_full	Evaluating the Performances of Biomarkers over a Restricted Domain of High Sensitivity
title_fullStr	Evaluating the Performances of Biomarkers over a Restricted Domain of High Sensitivity
title_full_unstemmed	Evaluating the Performances of Biomarkers over a Restricted Domain of High Sensitivity
title_sort	evaluating the performances of biomarkers over a restricted domain of high sensitivity
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/ac7ba9ebfd6949f59103c075332c5fa3
work_keys_str_mv	AT manuelfranco evaluatingtheperformancesofbiomarkersoverarestricteddomainofhighsensitivity AT juanamariavivo evaluatingtheperformancesofbiomarkersoverarestricteddomainofhighsensitivity
_version_	1718431904044154880

Evaluating the Performances of Biomarkers over a Restricted Domain of High Sensitivity

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