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Figure 4 from Clinical Validation of a Cell-Free DNA Fragmentome Assay for Augmentation of Lung Cancer Early Detection

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posted on 2024-11-01, 07:22 authored by Peter J. Mazzone, Peter B. Bach, Jacob Carey, Caitlin A. Schonewolf, Katalin Bognar, Manmeet S. Ahluwalia, Marcia Cruz-Correa, David Gierada, Sonali Kotagiri, Kathryn Lloyd, Fabien Maldonado, Jesse D. Ortendahl, Lecia V. Sequist, Gerard A. Silvestri, Nichole Tanner, Jeffrey C. Thompson, Anil Vachani, Kwok-Kin Wong, Ali H. Zaidi, Joseph Catallini, Ariel Gershman, Keith Lumbard, Laurel K. Millberg, Jeff Nawrocki, Carter Portwood, Aakanksha Rangnekar, Carolina Campos Sheridan, Niti Trivedi, Tony Wu, Yuhua Zong, Lindsey Cotton, Allison Ryan, Christopher Cisar, Alessandro Leal, Nicholas Dracopoli, Robert B. Scharpf, Victor E. Velculescu, Luke R. G. Pike

Performance of blood-based lung cancer screening test. A, Sensitivity and specificity of the test in the clinical validation set (N = 382) overall and by clinical subgroup. Point estimates are reported with 95% Wilson confidence intervals. Overall sensitivity and specificity denoted by solid vertical lines. B, Sensitivity of the test in the lung cancer cases in the clinical validation set (N = 248) evaluated across cancer histology, and T, N, and M categories. Point estimates are reported with 95% Wilson confidence intervals. Overall sensitivity of 84% denoted by the solid horizontal line. C, Left, sensitivity of the test in the lung cancer cases in the clinical validation set (N = 246) by cancer group stage. Middle, bar plot showing the stage distribution of lung cancer as observed in populations undergoing lung cancer screening with LDCT (based on NLST study) that are used to weigh observed stage-specific sensitivities. Right, lung cancer screening relevant stage-weighted sensitivity in clinical validation set. D, Comparison of the NNS with LDCT conditioned on test positive or negative result when applied in the lung cancer screening eligible population. Test performance showed consistency across clinical subgroups and expected increased performance with increasing burden of disease (tumor (T), node (N), metastasis (M) and group staging). After weighting, the stage distribution to reflect a screening population, test performance remained high and demonstrated the ability to reliably identify those individuals more likely to have lung cancer detected on LDCT.

Funding

Dr. Miriam and Sheldon G. Adelson Medical Research Foundation (AMRF)

Stand Up To Cancer (SU2C)

Gray Foundation

Honorable Tina Brozman Foundation (Tina’s Wish)

Commonwealth Foundation (CF)

Cole Foundation (CF)

History

ARTICLE ABSTRACT

Lung cancer screening via annual low-dose computed tomography has poor adoption. We conducted a prospective case–control study among 958 individuals eligible for lung cancer screening to develop a blood-based lung cancer detection test that when positive is followed by a low-dose computed tomography. Changes in genome-wide cell-free DNA fragmentation profiles (fragmentomes) in peripheral blood reflected genomic and chromatin characteristics of lung cancer. We applied machine learning to fragmentome features to identify individuals who were more or less likely to have lung cancer. We trained the classifier using 576 cases and controls from study samples and validated it in a held-out group of 382 cases and controls. The validation demonstrated high sensitivity for lung cancer and consistency across demographic groups and comorbid conditions. Applying test performance to the screening eligible population in a 5-year model with modest utilization assumptions suggested the potential to prevent thousands of lung cancer deaths.Significance: Lung cancer screening has poor adoption. Our study describes the development and validation of a novel blood-based lung cancer screening test utilizing a highly affordable, low-coverage genome-wide sequencing platform to analyze cell-free DNA fragmentation patterns. The test could improve lung cancer screening rates leading to substantial public health benefits.See related commentary by Haber and Skates, p. 2025