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Assessing Lung Cancer Absolute Risk Trajectory Based on a Polygenic Risk Model.
- Source :
-
Cancer research [Cancer Res] 2021 Mar 15; Vol. 81 (6), pp. 1607-1615. Date of Electronic Publication: 2021 Jan 20. - Publication Year :
- 2021
-
Abstract
- Lung cancer is the leading cause of cancer-related death globally. An improved risk stratification strategy can increase efficiency of low-dose CT (LDCT) screening. Here we assessed whether individual's genetic background has clinical utility for risk stratification in the context of LDCT screening. On the basis of 13,119 patients with lung cancer 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 on the basis of 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 ORs for individuals at the top decile of the PRS distribution versus those at bottom 10% was 2.39 [95% confidence interval (CI) = 1.92-3.00; P = 1.80 × 10 <superscript>-14</superscript> ] in the validation set ( P <subscript>trend</subscript> = 5.26 × 10 <superscript>-20</superscript> ). The OR per SD of PRS increase was 1.26 (95% CI = 1.20-1.32; P = 9.69 × 10 <superscript>-23</superscript> ) 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. SIGNIFICANCE: Three large-scale datasets reveal that, after accounting for risk factors, an individual's genetics can affect their lung cancer risk trajectory, thus may inform the optimal timing for LDCT screening.<br /> (©2021 American Association for Cancer Research.)
- Subjects :
- Adult
Age Factors
Aged
Case-Control Studies
Early Detection of Cancer standards
Early Detection of Cancer statistics & numerical data
Female
Genetic Predisposition to Disease
Genome-Wide Association Study
Humans
Incidence
Lung diagnostic imaging
Lung Neoplasms diagnosis
Lung Neoplasms genetics
Lung Neoplasms prevention & control
Machine Learning
Male
Mass Screening standards
Mass Screening statistics & numerical data
Medical History Taking
Middle Aged
Oligonucleotide Array Sequence Analysis
Practice Guidelines as Topic
Pulmonary Disease, Chronic Obstructive epidemiology
Risk Assessment methods
Risk Assessment statistics & numerical data
Risk Factors
Smoking epidemiology
Tomography, X-Ray Computed standards
Tomography, X-Ray Computed statistics & numerical data
United Kingdom epidemiology
Biomarkers, Tumor genetics
Lung Neoplasms epidemiology
Models, Genetic
Multifactorial Inheritance
Subjects
Details
- Language :
- English
- ISSN :
- 1538-7445
- Volume :
- 81
- Issue :
- 6
- Database :
- MEDLINE
- Journal :
- Cancer research
- Publication Type :
- Academic Journal
- Accession number :
- 33472890
- Full Text :
- https://doi.org/10.1158/0008-5472.CAN-20-1237