Clinical validation and utility of Percepta GSC for the evaluation of lung cancer

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  • Mazzone, Peter
    • Other Affiliation: Cleveland Clinic
  • Dotson, Travis
    • Other Affiliation: Wake Forest Baptist Health
  • Wahidi, Momen M.
    • Other Affiliation: Duke University Medical Center
  • Bernstein, Michael
    • Other Affiliation: Stamford Hospital
  • Lee, Hans J.
    • Other Affiliation: Johns Hopkins University
  • Kopman, David Feller
    • Other Affiliation: Johns Hopkins University
  • Yarmus, Lonny
    • Other Affiliation: Johns Hopkins University
  • Whitney, Duncan
    • Other Affiliation: Johnson & Johnson
  • Stevenson, Christopher
    • Other Affiliation: Johnson & Johnson
  • Qu, Jianghan
    • Other Affiliation: Veracyte, Inc.
  • Johnson, Marla
    • Other Affiliation: Veracyte, Inc.
  • Walsh, P. Sean
    • Other Affiliation: Veracyte, Inc.
  • Huang, Jing
    • Other Affiliation: Veracyte, Inc.
  • Lofaro, Lori R.
    • Other Affiliation: Veracyte, Inc.
  • Bhorade, Sangeeta M.
    • Other Affiliation: Veracyte, Inc.
  • Kennedy, Giulia C.
    • Other Affiliation: Veracyte, Inc.
  • Spira, Avrum
    • Other Affiliation: Boston University Medical Center
  • Rivera, M. Patricia
    • Affiliation: School of Medicine, Department of Medicine, Division of Pulmonary Diseases and Critical Care Medicine
  • The AEGIS Study Team
  • The Percepta Registry Investigators
Abstract
  • 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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  • Article
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  • In Copyright
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  • Attribution 4.0 International
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  • PLOS ONE
Journal volume
  • 17
Journal issue
  • 7
Page start
  • e0268567
Language
  • English
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  • Publisher
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  • 1932-6203

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