Decision theory for precision therapy of breast cancer

Abstract Correctly estimating the hormone receptor status for estrogen (ER) and progesterone (PGR) is crucial for precision therapy of breast cancer. It is known that conventional diagnostics (immunohistochemistry, IHC) yields a significant rate of wrongly diagnosed receptor status. Here we demonstr...

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Autores principales:	Michael Kenn, Dan Cacsire Castillo-Tong, Christian F. Singer, Rudolf Karch, Michael Cibena, Heinz Koelbl, Wolfgang Schreiner
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/db1c4ef44c7b4a4b8be90172f163f666
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spelling	oai:doaj.org-article:db1c4ef44c7b4a4b8be90172f163f6662021-12-02T14:21:43ZDecision theory for precision therapy of breast cancer10.1038/s41598-021-82418-72045-2322https://doaj.org/article/db1c4ef44c7b4a4b8be90172f163f6662021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-82418-7https://doaj.org/toc/2045-2322Abstract Correctly estimating the hormone receptor status for estrogen (ER) and progesterone (PGR) is crucial for precision therapy of breast cancer. It is known that conventional diagnostics (immunohistochemistry, IHC) yields a significant rate of wrongly diagnosed receptor status. Here we demonstrate how Dempster Shafer decision Theory (DST) enhances diagnostic precision by adding information from gene expression. We downloaded data of 3753 breast cancer patients from Gene Expression Omnibus. Information from IHC and gene expression was fused according to DST, and the clinical criterion for receptor positivity was re-modelled along DST. Receptor status predicted according to DST was compared with conventional assessment via IHC and gene-expression, and deviations were flagged as questionable. The survival of questionable cases turned out significantly worse (Kaplan Meier p < 1%) than for patients with receptor status confirmed by DST, indicating a substantial enhancement of diagnostic precision via DST. This study is not only relevant for precision medicine but also paves the way for introducing decision theory into OMICS data science.Michael KennDan Cacsire Castillo-TongChristian F. SingerRudolf KarchMichael CibenaHeinz KoelblWolfgang SchreinerNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Michael Kenn Dan Cacsire Castillo-Tong Christian F. Singer Rudolf Karch Michael Cibena Heinz Koelbl Wolfgang Schreiner Decision theory for precision therapy of breast cancer
description	Abstract Correctly estimating the hormone receptor status for estrogen (ER) and progesterone (PGR) is crucial for precision therapy of breast cancer. It is known that conventional diagnostics (immunohistochemistry, IHC) yields a significant rate of wrongly diagnosed receptor status. Here we demonstrate how Dempster Shafer decision Theory (DST) enhances diagnostic precision by adding information from gene expression. We downloaded data of 3753 breast cancer patients from Gene Expression Omnibus. Information from IHC and gene expression was fused according to DST, and the clinical criterion for receptor positivity was re-modelled along DST. Receptor status predicted according to DST was compared with conventional assessment via IHC and gene-expression, and deviations were flagged as questionable. The survival of questionable cases turned out significantly worse (Kaplan Meier p < 1%) than for patients with receptor status confirmed by DST, indicating a substantial enhancement of diagnostic precision via DST. This study is not only relevant for precision medicine but also paves the way for introducing decision theory into OMICS data science.
format	article
author	Michael Kenn Dan Cacsire Castillo-Tong Christian F. Singer Rudolf Karch Michael Cibena Heinz Koelbl Wolfgang Schreiner
author_facet	Michael Kenn Dan Cacsire Castillo-Tong Christian F. Singer Rudolf Karch Michael Cibena Heinz Koelbl Wolfgang Schreiner
author_sort	Michael Kenn
title	Decision theory for precision therapy of breast cancer
title_short	Decision theory for precision therapy of breast cancer
title_full	Decision theory for precision therapy of breast cancer
title_fullStr	Decision theory for precision therapy of breast cancer
title_full_unstemmed	Decision theory for precision therapy of breast cancer
title_sort	decision theory for precision therapy of breast cancer
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/db1c4ef44c7b4a4b8be90172f163f666
work_keys_str_mv	AT michaelkenn decisiontheoryforprecisiontherapyofbreastcancer AT dancacsirecastillotong decisiontheoryforprecisiontherapyofbreastcancer AT christianfsinger decisiontheoryforprecisiontherapyofbreastcancer AT rudolfkarch decisiontheoryforprecisiontherapyofbreastcancer AT michaelcibena decisiontheoryforprecisiontherapyofbreastcancer AT heinzkoelbl decisiontheoryforprecisiontherapyofbreastcancer AT wolfgangschreiner decisiontheoryforprecisiontherapyofbreastcancer
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Decision theory for precision therapy of breast cancer

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