Skip to Main Content

An official website of the United States government

Assessing Lung Cancer Absolute Risk Trajectory Based on a Polygenic Risk Model.

About this Publication
Title
Assessing Lung Cancer Absolute Risk Trajectory Based on a Polygenic Risk Model.
Pubmed ID
33472890 (View this publication on the PubMed website)
Digital Object Identifier
Publication
Cancer Res. 2021 Jan 20
Authors
Hung RJ, Warkentin MT, Brhane Y, Chatterjee N, Christiani DC, Landi MT, Caporaso NE, Liu G, Johansson M, Albanes D, Marchand LL, Tardon A, Rennert G, Bojesen SE, Chen C, Field JK, Kiemeney LA, Lazarus P, Zienolddiny S, Lam S, ...show more Andrew AS, Arnold SM, Aldrich MC, Bickeböller H, Risch A, Schabath MB, McKay JD, Brennan P, Amos CI
Affiliations
  • Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Canada. rayjean.hung@lunenfeld.ca.
  • Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Canada.
  • Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland.
  • Department of Environmental Health, Harvard TH Chan School of Public Health, and Massachusetts General Hospital/Harvard Medical School, Boston, Massachusetts.
  • Division of Cancer Epidemiology and Genetics, NCI, NIH, Bethesda, Maryland.
  • Princess Margaret Cancer Center, Toronto, Canada.
  • International Agency for Research on Cancer, Lyon, France.
  • University of Hawaii Cancer Center, Honolulu, Hawaii.
  • Universidad de Oviedo, ISPA and CIBERESP, Oviedo, Spain.
  • Department of Community Medicine and Epidemiology, Carmel Medical Center and B. Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel.
...show more
  • Herlev and Gentofte Hospital, Copenhagen, Denmark. Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Copenhagen, Denmark. Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
  • Fred Hutchinson Cancer Research Center, Seattle, Washington.
  • University of Liverpool Cancer Research Centre, Liverpool, United Kingdom.
  • Radboud University Nijmegen Medical Centre, Nijmegen, the Netherlands.
  • Washington State University, Spokane, Washington.
  • National Institute of Occupational Health, Oslo, Norway.
  • University of British Columbia, Vancouver, Canada.
  • Dartmouth Medical School, Hanover, New Hampshire.
  • Markey Cancer Center, Lexington, Kentucky.
  • Department of Thoracic Surgery, Division of Epidemiology, Vanderbilt University Medical Center, Nashville, Tennessee.
  • Department of Genetic Epidemiology, University Medical Center, Georg-August-University Göttingen, Göttingen, Germany.
  • University of Salzburg and Cancer Cluster Salzburg, Salzburg, Austria.
  • H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida.
  • Institute for Clinical and Translational Research, Baylor Medical College, Houston, Texas.
Abstract

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.

Related CDAS Studies
Related CDAS Projects