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Clinical validation and utility of Percepta GSC for the evaluation of lung cancer
The Percepta Genomic Sequencing Classifier (GSC) was developed to up-classify as well as down-classify the risk of malignancy for lung lesions when bronchoscopy is non-diagnostic. We evaluated the performance of Percepta GSC in risk re-classification of indeterminate lung lesions. This multicenter s...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9278743/ https://www.ncbi.nlm.nih.gov/pubmed/35830375 http://dx.doi.org/10.1371/journal.pone.0268567 |
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author | Mazzone, Peter Dotson, Travis Wahidi, Momen M. Bernstein, Michael Lee, Hans J. Feller Kopman, David Yarmus, Lonny Whitney, Duncan Stevenson, Christopher Qu, Jianghan Johnson, Marla Walsh, P. Sean Huang, Jing Lofaro, Lori R. Bhorade, Sangeeta M. Kennedy, Giulia C. Spira, Avrum Rivera, M. Patricia |
author_facet | Mazzone, Peter Dotson, Travis Wahidi, Momen M. Bernstein, Michael Lee, Hans J. Feller Kopman, David Yarmus, Lonny Whitney, Duncan Stevenson, Christopher Qu, Jianghan Johnson, Marla Walsh, P. Sean Huang, Jing Lofaro, Lori R. Bhorade, Sangeeta M. Kennedy, Giulia C. Spira, Avrum Rivera, M. Patricia |
author_sort | Mazzone, Peter |
collection | PubMed |
description | The Percepta Genomic Sequencing Classifier (GSC) was developed to up-classify as well as down-classify the risk of malignancy for lung lesions when bronchoscopy is non-diagnostic. We evaluated the performance of Percepta GSC in risk re-classification of indeterminate lung lesions. This multicenter study included individuals who currently or formerly smoked undergoing bronchoscopy for suspected lung cancer from the AEGIS I/ II cohorts and the Percepta Registry. The classifier was measured in normal-appearing bronchial epithelium from bronchial brushings. The sensitivity, specificity, and predictive values were calculated using predefined thresholds. The ability of the classifier to decrease unnecessary invasive procedures was estimated. A set of 412 patients were included in the validation (prevalence of malignancy was 39.6%). Overall, 29% of intermediate-risk lung lesions were down-classified to low-risk with a 91.0% negative predictive value (NPV) and 12.2% of intermediate-risk lesions were up-classified to high-risk with a 65.4% positive predictive value (PPV). In addition, 54.5% of low-risk lesions were down-classified to very low risk with >99% NPV and 27.3% of high-risk lesions were up-classified to very high risk with a 91.5% PPV. If the classifier results were used in nodule management, 50% of patients with benign lesions and 29% of patients with malignant lesions undergoing additional invasive procedures could have avoided these procedures. The Percepta GSC is highly accurate as both a rule-out and rule-in test. This high accuracy of risk re-classification may lead to improved management of lung lesions. |
format | Online Article Text |
id | pubmed-9278743 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-92787432022-07-14 Clinical validation and utility of Percepta GSC for the evaluation of lung cancer Mazzone, Peter Dotson, Travis Wahidi, Momen M. Bernstein, Michael Lee, Hans J. Feller Kopman, David Yarmus, Lonny Whitney, Duncan Stevenson, Christopher Qu, Jianghan Johnson, Marla Walsh, P. Sean Huang, Jing Lofaro, Lori R. Bhorade, Sangeeta M. Kennedy, Giulia C. Spira, Avrum Rivera, M. Patricia PLoS One Research Article The Percepta Genomic Sequencing Classifier (GSC) was developed to up-classify as well as down-classify the risk of malignancy for lung lesions when bronchoscopy is non-diagnostic. We evaluated the performance of Percepta GSC in risk re-classification of indeterminate lung lesions. This multicenter study included individuals who currently or formerly smoked undergoing bronchoscopy for suspected lung cancer from the AEGIS I/ II cohorts and the Percepta Registry. The classifier was measured in normal-appearing bronchial epithelium from bronchial brushings. The sensitivity, specificity, and predictive values were calculated using predefined thresholds. The ability of the classifier to decrease unnecessary invasive procedures was estimated. A set of 412 patients were included in the validation (prevalence of malignancy was 39.6%). Overall, 29% of intermediate-risk lung lesions were down-classified to low-risk with a 91.0% negative predictive value (NPV) and 12.2% of intermediate-risk lesions were up-classified to high-risk with a 65.4% positive predictive value (PPV). In addition, 54.5% of low-risk lesions were down-classified to very low risk with >99% NPV and 27.3% of high-risk lesions were up-classified to very high risk with a 91.5% PPV. If the classifier results were used in nodule management, 50% of patients with benign lesions and 29% of patients with malignant lesions undergoing additional invasive procedures could have avoided these procedures. The Percepta GSC is highly accurate as both a rule-out and rule-in test. This high accuracy of risk re-classification may lead to improved management of lung lesions. Public Library of Science 2022-07-13 /pmc/articles/PMC9278743/ /pubmed/35830375 http://dx.doi.org/10.1371/journal.pone.0268567 Text en © 2022 Mazzone et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Mazzone, Peter Dotson, Travis Wahidi, Momen M. Bernstein, Michael Lee, Hans J. Feller Kopman, David Yarmus, Lonny Whitney, Duncan Stevenson, Christopher Qu, Jianghan Johnson, Marla Walsh, P. Sean Huang, Jing Lofaro, Lori R. Bhorade, Sangeeta M. Kennedy, Giulia C. Spira, Avrum Rivera, M. Patricia Clinical validation and utility of Percepta GSC for the evaluation of lung cancer |
title | Clinical validation and utility of Percepta GSC for the evaluation of lung cancer |
title_full | Clinical validation and utility of Percepta GSC for the evaluation of lung cancer |
title_fullStr | Clinical validation and utility of Percepta GSC for the evaluation of lung cancer |
title_full_unstemmed | Clinical validation and utility of Percepta GSC for the evaluation of lung cancer |
title_short | Clinical validation and utility of Percepta GSC for the evaluation of lung cancer |
title_sort | clinical validation and utility of percepta gsc for the evaluation of lung cancer |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9278743/ https://www.ncbi.nlm.nih.gov/pubmed/35830375 http://dx.doi.org/10.1371/journal.pone.0268567 |
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