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Percepta Genomic Sequencing Classifier and decision-making in patients with high-risk lung nodules: a decision impact study

BACKGROUND: Incidental and screening-identified lung nodules are common, and a bronchoscopic evaluation is frequently nondiagnostic. The Percepta Genomic Sequencing Classifier (GSC) is a genomic classifier developed in current and former smokers which can be used for further risk stratification in t...

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Autores principales: Sethi, Sonali, Oh, Scott, Chen, Alexander, Bellinger, Christina, Lofaro, Lori, Johnson, Marla, Huang, Jing, Bhorade, Sangeeta Maruti, Bulman, William, Kennedy, Giulia C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8740045/
https://www.ncbi.nlm.nih.gov/pubmed/34991528
http://dx.doi.org/10.1186/s12890-021-01772-4
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author Sethi, Sonali
Oh, Scott
Chen, Alexander
Bellinger, Christina
Lofaro, Lori
Johnson, Marla
Huang, Jing
Bhorade, Sangeeta Maruti
Bulman, William
Kennedy, Giulia C.
author_facet Sethi, Sonali
Oh, Scott
Chen, Alexander
Bellinger, Christina
Lofaro, Lori
Johnson, Marla
Huang, Jing
Bhorade, Sangeeta Maruti
Bulman, William
Kennedy, Giulia C.
author_sort Sethi, Sonali
collection PubMed
description BACKGROUND: Incidental and screening-identified lung nodules are common, and a bronchoscopic evaluation is frequently nondiagnostic. The Percepta Genomic Sequencing Classifier (GSC) is a genomic classifier developed in current and former smokers which can be used for further risk stratification in these patients. Percepta GSC has the capability of up-classifying patients with a pre-bronchoscopy risk that is high (> 60%) to “very high risk” with a positive predictive value of 91.5%. This prospective, randomized decision impact survey was designed to test the hypothesis that an up-classification of risk of malignancy from high to very high will increase the rate of referral for surgical or ablative therapy without additional intervening procedures while increasing physician confidence. METHODS: Data were collected from 37 cases from the Percepta GSC validation cohort in which the pre-bronchoscopy risk of malignancy was high (> 60%), the bronchoscopy was nondiagnostic, and the patient was up-classified to very high risk by Percepta GSC. The cases were randomly presented to U.S pulmonologists in three formats: a pre-post cohort where each case is presented initially without and then with a GSG result, and two independent cohorts where each case is presented either with or without with a GSC result. Physicians were surveyed with respect to subsequent management steps and confidence in that decision. RESULTS: One hundred and one survey takers provided a total of 1341 evaluations of the 37 patient cases across the three different cohorts. The rate of recommendation for surgical resection was significantly higher in the independent cohort with a GSC result compared to the independent cohort without a GSC result (45% vs. 17%, p < 0.001) In the pre-post cross-over cohort, the rate increased from 17 to 56% (p < 0.001) following the review of the GSC result. A GSC up-classification from high to very high risk of malignancy increased Pulmonologists’ confidence in decision-making following a nondiagnostic bronchoscopy. CONCLUSIONS: Use of the Percepta GSC classifier will allow more patients with early lung cancer to proceed more rapidly to potentially curative therapy while decreasing unnecessary intervening diagnostic procedures following a nondiagnostic bronchoscopy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12890-021-01772-4.
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spelling pubmed-87400452022-01-07 Percepta Genomic Sequencing Classifier and decision-making in patients with high-risk lung nodules: a decision impact study Sethi, Sonali Oh, Scott Chen, Alexander Bellinger, Christina Lofaro, Lori Johnson, Marla Huang, Jing Bhorade, Sangeeta Maruti Bulman, William Kennedy, Giulia C. BMC Pulm Med Research BACKGROUND: Incidental and screening-identified lung nodules are common, and a bronchoscopic evaluation is frequently nondiagnostic. The Percepta Genomic Sequencing Classifier (GSC) is a genomic classifier developed in current and former smokers which can be used for further risk stratification in these patients. Percepta GSC has the capability of up-classifying patients with a pre-bronchoscopy risk that is high (> 60%) to “very high risk” with a positive predictive value of 91.5%. This prospective, randomized decision impact survey was designed to test the hypothesis that an up-classification of risk of malignancy from high to very high will increase the rate of referral for surgical or ablative therapy without additional intervening procedures while increasing physician confidence. METHODS: Data were collected from 37 cases from the Percepta GSC validation cohort in which the pre-bronchoscopy risk of malignancy was high (> 60%), the bronchoscopy was nondiagnostic, and the patient was up-classified to very high risk by Percepta GSC. The cases were randomly presented to U.S pulmonologists in three formats: a pre-post cohort where each case is presented initially without and then with a GSG result, and two independent cohorts where each case is presented either with or without with a GSC result. Physicians were surveyed with respect to subsequent management steps and confidence in that decision. RESULTS: One hundred and one survey takers provided a total of 1341 evaluations of the 37 patient cases across the three different cohorts. The rate of recommendation for surgical resection was significantly higher in the independent cohort with a GSC result compared to the independent cohort without a GSC result (45% vs. 17%, p < 0.001) In the pre-post cross-over cohort, the rate increased from 17 to 56% (p < 0.001) following the review of the GSC result. A GSC up-classification from high to very high risk of malignancy increased Pulmonologists’ confidence in decision-making following a nondiagnostic bronchoscopy. CONCLUSIONS: Use of the Percepta GSC classifier will allow more patients with early lung cancer to proceed more rapidly to potentially curative therapy while decreasing unnecessary intervening diagnostic procedures following a nondiagnostic bronchoscopy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12890-021-01772-4. BioMed Central 2022-01-06 /pmc/articles/PMC8740045/ /pubmed/34991528 http://dx.doi.org/10.1186/s12890-021-01772-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Sethi, Sonali
Oh, Scott
Chen, Alexander
Bellinger, Christina
Lofaro, Lori
Johnson, Marla
Huang, Jing
Bhorade, Sangeeta Maruti
Bulman, William
Kennedy, Giulia C.
Percepta Genomic Sequencing Classifier and decision-making in patients with high-risk lung nodules: a decision impact study
title Percepta Genomic Sequencing Classifier and decision-making in patients with high-risk lung nodules: a decision impact study
title_full Percepta Genomic Sequencing Classifier and decision-making in patients with high-risk lung nodules: a decision impact study
title_fullStr Percepta Genomic Sequencing Classifier and decision-making in patients with high-risk lung nodules: a decision impact study
title_full_unstemmed Percepta Genomic Sequencing Classifier and decision-making in patients with high-risk lung nodules: a decision impact study
title_short Percepta Genomic Sequencing Classifier and decision-making in patients with high-risk lung nodules: a decision impact study
title_sort percepta genomic sequencing classifier and decision-making in patients with high-risk lung nodules: a decision impact study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8740045/
https://www.ncbi.nlm.nih.gov/pubmed/34991528
http://dx.doi.org/10.1186/s12890-021-01772-4
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