Screening promotes early detection of cancer to decrease mortality. Unfortunately, significant racial disparities
exist in lung cancer screening. Recently published findings by our team show that under current national
screening guidelines African Americans have reduced eligibility for lung cancer screening compared to whites.
These screening guidelines are based on a combination of age and smoking pack-year criteria derived from a
national lung screening trial that was primarily (91%) white. Importantly, smoking behaviors and baseline risks
for lung cancer differ greatly between African Americans and whites. Because of this, a risk-based screening
strategy may provide a more equitable assessment of eligibility than current screening guidelines. However, the
development of personalized risk prediction models for lung cancer in African Americans has been limited. To
address this gap and to improve equity in screening eligibility, we propose building a personalized prediction tool
using the combined data from three large-scale population-based prospective cohorts with substantial African
American representation. The combined cohorts have over 336,000 individuals (44% African American) and
9,132 incident lung cancer cases from across the United States. We propose the following three aims: 1)
construct a well-calibrated natural-history model of lung cancer risk for screening in African Americans, 2)
evaluate lung cancer screening strategies by simulation and identify sub-populations who would benefit from
screening, accounting for comorbidities and false-positives, and 3) develop a web-based decision aid for
screening that is culturally appropriate. We will employ innovative machine learning techniques and state-of-the-
art statistical methods to build a well-calibrated lung cancer prediction model for African Americans. Careful
examination will identify sub-populations (such as women, low socioeconomic status, rural, age groups, etc.)
that will benefit from screening. A key innovative aspect of this proposal is its community-engaged approach and
partnership with a Community Advisory Board, both of which will help translate our empirical findings into the
design of a patient-oriented decision aid. This project is relevant to the mission of the National Cancer Institute
since it focuses on establishing equity in lung cancer screening eligibility. Our findings will have sustained impact
on precision health and motivate improved clinical strategies for the early detection of lung cancer for African
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