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Buccal Spectral Markers for Lung Cancer Risk Stratification

Lung cancer remains the leading cause of cancer deaths in the US with >150,000 deaths per year. In order to more effectively reduce lung cancer mortality, more sophisticated screening paradigms are needed. Previously, our group demonstrated the use of low-coherence enhanced backscattering (LEBS)...

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Autores principales: Radosevich, Andrew J., Mutyal, Nikhil N., Rogers, Jeremy D., Gould, Bradley, Hensing, Thomas A., Ray, Daniel, Backman, Vadim, Roy, Hemant K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4192585/
https://www.ncbi.nlm.nih.gov/pubmed/25299667
http://dx.doi.org/10.1371/journal.pone.0110157
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author Radosevich, Andrew J.
Mutyal, Nikhil N.
Rogers, Jeremy D.
Gould, Bradley
Hensing, Thomas A.
Ray, Daniel
Backman, Vadim
Roy, Hemant K.
author_facet Radosevich, Andrew J.
Mutyal, Nikhil N.
Rogers, Jeremy D.
Gould, Bradley
Hensing, Thomas A.
Ray, Daniel
Backman, Vadim
Roy, Hemant K.
author_sort Radosevich, Andrew J.
collection PubMed
description Lung cancer remains the leading cause of cancer deaths in the US with >150,000 deaths per year. In order to more effectively reduce lung cancer mortality, more sophisticated screening paradigms are needed. Previously, our group demonstrated the use of low-coherence enhanced backscattering (LEBS) spectroscopy to detect and quantify the micro/nano-architectural correlates of colorectal and pancreatic field carcinogenesis. In the lung, the buccal (cheek) mucosa has been suggested as an excellent surrogate site in the “field of injury”. We, therefore, wanted to assess whether LEBS could similarly sense the presence of lung. To this end, we applied a fiber-optic LEBS probe to a dataset of 27 smokers without diagnosed lung cancer (controls) and 46 with lung cancer (cases), which was divided into a training and a blinded validation set (32 and 41 subjects, respectively). LEBS readings of the buccal mucosa were taken from the oral cavity applying gentle contact. The diagnostic LEBS marker was notably altered in patients harboring lung cancer compared to smoking controls. The prediction rule developed on training set data provided excellent diagnostics with 94% sensitivity, 80% specificity, and 95% accuracy. Applying the same threshold to the blinded validation set yielded 79% sensitivity and 83% specificity. These results were not confounded by patient demographics or impacted by cancer type or location. Moreover, the prediction rule was robust across all stages of cancer including stage I. We envision the use of LEBS as the first part of a two-step paradigm shift in lung cancer screening in which patients with high LEBS risk markers are funnelled into more invasive screening for confirmation.
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spelling pubmed-41925852014-10-14 Buccal Spectral Markers for Lung Cancer Risk Stratification Radosevich, Andrew J. Mutyal, Nikhil N. Rogers, Jeremy D. Gould, Bradley Hensing, Thomas A. Ray, Daniel Backman, Vadim Roy, Hemant K. PLoS One Research Article Lung cancer remains the leading cause of cancer deaths in the US with >150,000 deaths per year. In order to more effectively reduce lung cancer mortality, more sophisticated screening paradigms are needed. Previously, our group demonstrated the use of low-coherence enhanced backscattering (LEBS) spectroscopy to detect and quantify the micro/nano-architectural correlates of colorectal and pancreatic field carcinogenesis. In the lung, the buccal (cheek) mucosa has been suggested as an excellent surrogate site in the “field of injury”. We, therefore, wanted to assess whether LEBS could similarly sense the presence of lung. To this end, we applied a fiber-optic LEBS probe to a dataset of 27 smokers without diagnosed lung cancer (controls) and 46 with lung cancer (cases), which was divided into a training and a blinded validation set (32 and 41 subjects, respectively). LEBS readings of the buccal mucosa were taken from the oral cavity applying gentle contact. The diagnostic LEBS marker was notably altered in patients harboring lung cancer compared to smoking controls. The prediction rule developed on training set data provided excellent diagnostics with 94% sensitivity, 80% specificity, and 95% accuracy. Applying the same threshold to the blinded validation set yielded 79% sensitivity and 83% specificity. These results were not confounded by patient demographics or impacted by cancer type or location. Moreover, the prediction rule was robust across all stages of cancer including stage I. We envision the use of LEBS as the first part of a two-step paradigm shift in lung cancer screening in which patients with high LEBS risk markers are funnelled into more invasive screening for confirmation. Public Library of Science 2014-10-09 /pmc/articles/PMC4192585/ /pubmed/25299667 http://dx.doi.org/10.1371/journal.pone.0110157 Text en © 2014 Radosevich et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Radosevich, Andrew J.
Mutyal, Nikhil N.
Rogers, Jeremy D.
Gould, Bradley
Hensing, Thomas A.
Ray, Daniel
Backman, Vadim
Roy, Hemant K.
Buccal Spectral Markers for Lung Cancer Risk Stratification
title Buccal Spectral Markers for Lung Cancer Risk Stratification
title_full Buccal Spectral Markers for Lung Cancer Risk Stratification
title_fullStr Buccal Spectral Markers for Lung Cancer Risk Stratification
title_full_unstemmed Buccal Spectral Markers for Lung Cancer Risk Stratification
title_short Buccal Spectral Markers for Lung Cancer Risk Stratification
title_sort buccal spectral markers for lung cancer risk stratification
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4192585/
https://www.ncbi.nlm.nih.gov/pubmed/25299667
http://dx.doi.org/10.1371/journal.pone.0110157
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