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Tundra lists 3 Family History of Lung Cancer clinical trials. Each listing includes eligibility criteria, study locations, and direct links to research sites in the Tundra directory.
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NCT07838519
Personalizing Veterans' Lung Cancer Screening and Diagnosis
Lung cancer screening with low-dose chest computed tomography (CT) is currently recommended for high-risk individuals who are 50 to 80 years old, have smoked cigarettes for at least 20 pack-years, and currently smoke or quit smoking within the past 15 years. In a prospective cohort at Nashville, Denver, Louisville, Chicago, Kansas City, Salisbury and Seattle Veteran Affairs medical centers, the investigators will evaluate the detection of lung cancer using an expanded screening eligibility criteria based on Veterans' personal and service-related exposures compared to standard of care criteria. Screening a larger population will increase the number of lung nodules needing clinical management and these nodules may or may not be cancer. In a population of Veterans with positive screenings at Nashville, the investigators will also validate a combination biomarker-based approach to manage screen-detected lung nodules to reduce time to lung cancer diagnosis and use of invasive procedures. This study will also convene a Veteran Community Advisory Board and interview Veterans to better understand their thoughts about lung cancer screening and preferences for outreach and engagement.
Gender: All
Ages: 50 Years - 80 Years
Updated: 2026-09-30
7 states
NCT07600801
LEGACY: Lung Cancer Screening in Individuals With a Lung Cancer Family History-Protocol B
This research is being done to determine if an image-based deep learning model (Sybil) can accurately predict the likelihood of future lung cancer based on chest computed tomography (CT) imaging from individuals with a family history of lung cancer.
Gender: All
Ages: 18 Years - Any
Updated: 2026-08-25
1 state
NCT07685028
LEGACY: Lung Cancer Screening in Individuals With a Lung Cancer Family History-Protocol A
This research is being done to determine if an image-based deep learning model (Sybil) can accurately predict the likelihood of future lung cancer based on chest computed tomography (CT) imaging from individuals.
Gender: All
Ages: 18 Years - 80 Years
Updated: 2026-07-06
1 state