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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
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.
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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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