Salivary biomarkers for cancer diagnosis: a meta-analysis

Background: Saliva represents a promising non-invasive source of novel biomarkers for diagnosis and prognosis cancer. This meta-analysis evaluates the diagnostic value of salivary biomarkers for detection of malignant non-oral tumours to better define the value of saliva as an alternative liquid bio...

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Autores: Rapado González, Óscar, Martínez-Reglero, Cristina, Salgado-Barreira, Ángel, Takkouche, Bahi, López López, Rafael, Suárez Cunqueiro, María Mercedes, Muinelo-Romay, Laura
Tipo de recurso: artículo
Fecha de publicación:2020
País:España
Institución:Universidad de Santiago de Compostela (USC)
Repositorio:Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela
Idioma:inglés
OAI Identifier:oai:minerva.usc.gal:10347/43762
Acceso en línea:https://hdl.handle.net/10347/43762
Access Level:acceso abierto
Palabra clave:saliva
salivary biomarkers
salivaomics
cancer
diagnosis
liquid biopsy
meta-analysis
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spelling Salivary biomarkers for cancer diagnosis: a meta-analysisRapado González, ÓscarMartínez-Reglero, CristinaSalgado-Barreira, ÁngelTakkouche, BahiLópez López, RafaelSuárez Cunqueiro, María MercedesMuinelo-Romay, Laurasalivasalivary biomarkerssalivaomicscancerdiagnosisliquid biopsymeta-analysisBackground: Saliva represents a promising non-invasive source of novel biomarkers for diagnosis and prognosis cancer. This meta-analysis evaluates the diagnostic value of salivary biomarkers for detection of malignant non-oral tumours to better define the value of saliva as an alternative liquid biopsy. Materials and methods: We performed a systematic review and meta-analysis. PubMed, Embase, LILACS and the Cochrane Library were searched to identify articles that examined the potential of salivary biomarkers for the diagnosis of malignant non-oral tumours. To assess the overall accuracy, we calculated the diagnostic odds ratio (DOR), area under hierarchical summary receiver operating characteristic (AUC) curve, sensitivity, specificity, positive likelihood ratio (PLR) and negative likelihood ratio (NLR) using a random- or fixed-effects model. Heterogeneity and publication bias were assessed. Statistical tests were two-sided. Results: One hundred fifty-five study units from 29 articles with 11,153 subjects were included. The pooled sensitivity, specificity, PLR, NLR, DOR and AUC were 0.76 (95% confidence intervals (CI), 0.74–0.77), 0.76 (95% CI, 0.75–0.77), 3.22 (95% CI, 2.92–3.55), 0.31 (95% CI, 0.28–0.34), 13.42 (95% CI, 12.28–15.96) and 0.85 (95% CI, 0.84–0.87), respectively. Conclusion: Salivary biomarkers may be potentially used for non-invasive diagnosis of malignant non-oral tumours.Taylor and FrancisUniversidade de Santiago de Compostela. Departamento de Psiquiatría, Radioloxía, Saúde Pública, Enfermaría e MedicinaUniversidade de Santiago de Compostela. Departamento de Cirurxía e Especialidades Médico-Cirúrxicas20202020-04-1120202020-04-11journal articlehttp://purl.org/coar/resource_type/c_6501AMhttp://purl.org/coar/version/c_ab4af688f83e57aainfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/10347/43762reponame:Minerva. Repositorio Institucional de la Universidad de Santiago de Compostelainstname:Universidad de Santiago de Compostela (USC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2©2020 Informa UK Limited, trading as Taylor & Francis Grouphttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:minerva.usc.gal:10347/437622026-06-15T12:47:27Z
dc.title.none.fl_str_mv Salivary biomarkers for cancer diagnosis: a meta-analysis
title Salivary biomarkers for cancer diagnosis: a meta-analysis
spellingShingle Salivary biomarkers for cancer diagnosis: a meta-analysis
Rapado González, Óscar
saliva
salivary biomarkers
salivaomics
cancer
diagnosis
liquid biopsy
meta-analysis
title_short Salivary biomarkers for cancer diagnosis: a meta-analysis
title_full Salivary biomarkers for cancer diagnosis: a meta-analysis
title_fullStr Salivary biomarkers for cancer diagnosis: a meta-analysis
title_full_unstemmed Salivary biomarkers for cancer diagnosis: a meta-analysis
title_sort Salivary biomarkers for cancer diagnosis: a meta-analysis
dc.creator.none.fl_str_mv Rapado González, Óscar
Martínez-Reglero, Cristina
Salgado-Barreira, Ángel
Takkouche, Bahi
López López, Rafael
Suárez Cunqueiro, María Mercedes
Muinelo-Romay, Laura
author Rapado González, Óscar
author_facet Rapado González, Óscar
Martínez-Reglero, Cristina
Salgado-Barreira, Ángel
Takkouche, Bahi
López López, Rafael
Suárez Cunqueiro, María Mercedes
Muinelo-Romay, Laura
author_role author
author2 Martínez-Reglero, Cristina
Salgado-Barreira, Ángel
Takkouche, Bahi
López López, Rafael
Suárez Cunqueiro, María Mercedes
Muinelo-Romay, Laura
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade de Santiago de Compostela. Departamento de Psiquiatría, Radioloxía, Saúde Pública, Enfermaría e Medicina
Universidade de Santiago de Compostela. Departamento de Cirurxía e Especialidades Médico-Cirúrxicas
dc.subject.none.fl_str_mv saliva
salivary biomarkers
salivaomics
cancer
diagnosis
liquid biopsy
meta-analysis
topic saliva
salivary biomarkers
salivaomics
cancer
diagnosis
liquid biopsy
meta-analysis
description Background: Saliva represents a promising non-invasive source of novel biomarkers for diagnosis and prognosis cancer. This meta-analysis evaluates the diagnostic value of salivary biomarkers for detection of malignant non-oral tumours to better define the value of saliva as an alternative liquid biopsy. Materials and methods: We performed a systematic review and meta-analysis. PubMed, Embase, LILACS and the Cochrane Library were searched to identify articles that examined the potential of salivary biomarkers for the diagnosis of malignant non-oral tumours. To assess the overall accuracy, we calculated the diagnostic odds ratio (DOR), area under hierarchical summary receiver operating characteristic (AUC) curve, sensitivity, specificity, positive likelihood ratio (PLR) and negative likelihood ratio (NLR) using a random- or fixed-effects model. Heterogeneity and publication bias were assessed. Statistical tests were two-sided. Results: One hundred fifty-five study units from 29 articles with 11,153 subjects were included. The pooled sensitivity, specificity, PLR, NLR, DOR and AUC were 0.76 (95% confidence intervals (CI), 0.74–0.77), 0.76 (95% CI, 0.75–0.77), 3.22 (95% CI, 2.92–3.55), 0.31 (95% CI, 0.28–0.34), 13.42 (95% CI, 12.28–15.96) and 0.85 (95% CI, 0.84–0.87), respectively. Conclusion: Salivary biomarkers may be potentially used for non-invasive diagnosis of malignant non-oral tumours.
publishDate 2020
dc.date.none.fl_str_mv 2020
2020-04-11
2020
2020-04-11
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
AM
http://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/10347/43762
url https://hdl.handle.net/10347/43762
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
©2020 Informa UK Limited, trading as Taylor & Francis Group
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
©2020 Informa UK Limited, trading as Taylor & Francis Group
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Taylor and Francis
publisher.none.fl_str_mv Taylor and Francis
dc.source.none.fl_str_mv reponame:Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela
instname:Universidad de Santiago de Compostela (USC)
instname_str Universidad de Santiago de Compostela (USC)
reponame_str Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela
collection Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.812429

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