Lung cancer is the leading cause of cancer death globally. An improved risk stratification strategy can increase efficiency of low-dose computed tomography (LDCT) screening. Here we assessed whether individual's genetic background has clinical utility for risk stratification in the context of LDCT screening. Based on 13,119 lung cancer patients and 10,008 controls with European ancestry in the International Lung Cancer Consortium, we constructed a polygenic risk score (PRS) via 10-fold cross-validation with regularized penalized regression. The performance of risk model integrating PRS, including calibration and ability to discriminate, was assessed using UK biobank data (N=335,931). Absolute risk was estimated based on age-specific lung cancer incidence and all-cause mortality as competing risk. To evaluate its potential clinical utility, the PRS distribution was simulated in the National Lung Screening Trial, N=50,772 participants). The lung cancer odds ratio (ORs) for individuals at the top decile of the PRS distribution versus those at bottom 10% was 2.39 (95%CI=1.92-3.00, P=1.80x10-14) in the validation set (trend p-value of 5.26 x 10-20). The OR per standard deviation of PRS increase was 1.26 (95%CI=1.20-1.32, P=9.69x10-23) for overall lung cancer risk in the validation set. When considering absolute risks, individuals at different PRS deciles showed differential trajectories of 5-year and cumulative absolute risk. The age reaching the LDCT screening recommendation threshold can vary by 4 to 8 years, depending on the individual's genetic background, smoking status and family history. Collectively, these results suggest that Individual's genetic background may inform the optimal lung cancer LDCT screening strategy.
Bibliographical noteCopyright ©2021, American Association for Cancer Research.
Fields of Science and Technology Classification 2012
- 303 Health Sciences
- lung Cancer
- risk prediction
- absolute risk
- polygenic risk score