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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 Population health benefits of a blood-based test in lung cancer screening. A, Care pathway reflecting the recommended standard of care for lung cancer screening with LDCT that is received by 6%–10% of eligible individuals annually, as well as potential pathway employing initial blood-based test and follow-on events. B, The predicted number of cancers detected by screening scenario: LDCT alone (“base case”); LDCT + low test uptake; LDCT + high test uptake. C, Predicted cancers diagnosed at stage I versus Stage IV by screening scenario: LDCT alone (“base case”); LDCT + low test uptake; LDCT + high test uptake. D, Predicted decrease in lung cancer deaths represented by screening scenario: LDCT alone (“base case”); LDCT + low test uptake; LDCT + high test uptake. E, Simulated comparison of the predicted number needed to scan with LDCT to detect one lung cancer: LDCT alone (“base case”); LDCT + low test uptake; LDCT + high test uptake. Population-level modeling demonstrates significant health benefits when a blood-based test is available as an alternative for lung cancer screening.
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
