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Assessing Lung Cancer Absolute Risk Trajectory based on a Polygenic Risk Model.
Hung, Rayjean J; Warkentin, Matthew T; Brhane, Yonathan; Chatterjee, Nilanjan; Christiani, David C; Landi, Maria Teresa; Caporaso, Neil E; Liu, Geoffrey; Johansson, Mattias; Albanes, Demetrius; Le Marchand, Loic; Tardon, Adonina; Rennert, Gad; Bojesen, Stig E; Chen, Chu; Field, John K; Kiemeney, Lambertus A; Lazarus, Philip; Zienolddiny, Shanbeh; Lam, Stephen; Andrew, Angeline S; Arnold, Susanne M; Aldrich, Melinda C; Bickeböller, Heike; Risch, Angela; Schabath, Matthew B; McKay, James D; Brennan, Paul; Amos, Christopher I.
Afiliação
  • Hung RJ; Lunenfeld Tanenbaum Research Institute, Sinai Health System rayjean.hung@lunenfeld.ca.
  • Warkentin MT; Lunenfeld-Tanenbaum Research Institute, Sinai Health System.
  • Brhane Y; Lunenfeld-Tanenbaum Research Institute, Sinai Health System.
  • Chatterjee N; Biostatistics and Oncology, Johns Hopkins University.
  • Christiani DC; Environmental Health, Harvard School of Public Health.
  • Landi MT; Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, DHHS.
  • Caporaso NE; Division of Cancer Epidemiology & Genetics, National Cancer Institute.
  • Liu G; Medical Oncology, Princess Margaret Cancer Centre, University of Toronto.
  • Johansson M; Genetic Epidemiology, International Agency For Research On Cancer.
  • Albanes D; Division of Cancer Epidemiology and Genetics, National Cancer Institute.
  • Le Marchand L; Department of Epidemiology, University of Hawaii Cancer Center.
  • Tardon A; Medicina, Universidad de Oviedo, Public Health Department.
  • Rennert G; Department of Community Medicine & Epidemiology; Clalit National Cancer Control Center, Lady Davis Carmel Medical Center, Ruth & Bruce Rappaport Faculty of Medicine, Technion-Israel Institute of Technology.
  • Bojesen SE; Clinical Biochemistry, Copenhagen University Hospital and University of Copenhagen.
  • Chen C; Program in Epidemiology, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center.
  • Field JK; Department of Molecular and Clinical Cancer Medicine, University of Liverpool.
  • Kiemeney LA; Department for Health Evidence, Radboud University Medical Centre.
  • Lazarus P; Pharmaceutical Sciences, College of Pharmacy and Pharmaceutical Sciences, Washington State University.
  • Zienolddiny S; Section for Toxicology, National Institute of Occupational Health.
  • Lam S; Integrative Oncology, British Columbia Cancer Agency.
  • Andrew AS; Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth.
  • Arnold SM; Markey Cancer Center, University of Kentucky.
  • Aldrich MC; Genetic Medicine, Vanderbilt University Medical Center.
  • Bickeböller H; Department of Genetic Epidemiology, University Medical Center, Georg-August-University Göttingen.
  • Risch A; Department of Biosciences, Allergy-Cancer-BioNano Research Centre and Cancer Cluster Salzburg, University of Salzburg.
  • Schabath MB; Department of Cancer Epidemiology, Moffitt Cancer Center.
  • McKay JD; Genetic Cancer Susceptibility Group, International Agency For Research On Cancer.
  • Brennan P; Genetic Epidemiology, International Agency For Research On Cancer.
  • Amos CI; Institute for Clinical and Translational Research, Baylor College of Medicine.
Cancer Res ; 2021 Jan 20.
Artigo em Inglês | MEDLINE | ID: mdl-33472890
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.
Texto completo: Disponível Coleções: Bases de dados internacionais Base de dados: MEDLINE Tipo de estudo: Estudo de etiologia / Estudo prognóstico / Fatores de risco Idioma: Inglês Ano de publicação: 2021 Tipo de documento: Artigo

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Texto completo: Disponível Coleções: Bases de dados internacionais Base de dados: MEDLINE Tipo de estudo: Estudo de etiologia / Estudo prognóstico / Fatores de risco Idioma: Inglês Ano de publicação: 2021 Tipo de documento: Artigo