Targeting lung cancer screening to individuals at greatest risk: the role of genetic factorsCitation formats

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Targeting lung cancer screening to individuals at greatest risk: the role of genetic factors. / Lebrett, Mikey; Crosbie, Emma; Smith, Miriam J; Woodward, Emma; Evans, D Gareth; Crosbie, Philip.

In: Journal of Medical Genetics, 29.01.2021.

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@article{e146b4161dcc42f0995dd57c4128fb98,
title = "Targeting lung cancer screening to individuals at greatest risk: the role of genetic factors",
abstract = "Lung cancer (LC) is the most common global cancer. An individual{\textquoteright}s risk of developing LC is mediated by an array of factors, including family history of the disease. Considerable research into genetic risk factors for LC has taken place in recent years, with both low and high-penetrance variants implicated in increasing or decreasing a person{\textquoteright}s risk of the disease. LC is the leading cause of cancer death worldwide; poor survival is driven by late onset of non-specific symptoms, resulting in late-stage diagnoses. Evidence for the efficacy of screening in detecting cancer earlier, thereby reducing lung-cancer specific mortality, is now well established. To ensure the cost-effectiveness of a screening programme, and to limit the potential harms to participants, a risk threshold for screening eligibility is required. Risk prediction models (RPM), which provide an individual{\textquoteright}s personal risk of LC over a particular period based on a large number of risk factors, may improve the selection of high-risk individuals for LC screening when compared with generalised eligibility criteria which only consider smoking history and age. No currently used RPM integrates genetic risk factors into its calculation of risk. This review provides an overview of the evidence for LC screening, screening related harms and the use of RPMs in screening cohort selection. It gives a synopsis of the known genetic risk factors for lung cancer, and discusses the evidence for including them in RPMs, focussing in particular on the use of polygenic risk scores to increase the accuracy of targeted lung cancer screening. ",
author = "Mikey Lebrett and Emma Crosbie and Smith, {Miriam J} and Emma Woodward and Evans, {D Gareth} and Philip Crosbie",
note = "Publisher Copyright: {\textcopyright} Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.",
year = "2021",
month = jan,
day = "29",
doi = "http://dx.doi.org/10.1136/jmedgenet-2020-107399",
language = "English",
journal = "Journal of Medical Genetics",
issn = "1468-6244",
publisher = "BMJ ",

}

RIS

TY - JOUR

T1 - Targeting lung cancer screening to individuals at greatest risk: the role of genetic factors

AU - Lebrett, Mikey

AU - Crosbie, Emma

AU - Smith, Miriam J

AU - Woodward, Emma

AU - Evans, D Gareth

AU - Crosbie, Philip

N1 - Publisher Copyright: © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

PY - 2021/1/29

Y1 - 2021/1/29

N2 - Lung cancer (LC) is the most common global cancer. An individual’s risk of developing LC is mediated by an array of factors, including family history of the disease. Considerable research into genetic risk factors for LC has taken place in recent years, with both low and high-penetrance variants implicated in increasing or decreasing a person’s risk of the disease. LC is the leading cause of cancer death worldwide; poor survival is driven by late onset of non-specific symptoms, resulting in late-stage diagnoses. Evidence for the efficacy of screening in detecting cancer earlier, thereby reducing lung-cancer specific mortality, is now well established. To ensure the cost-effectiveness of a screening programme, and to limit the potential harms to participants, a risk threshold for screening eligibility is required. Risk prediction models (RPM), which provide an individual’s personal risk of LC over a particular period based on a large number of risk factors, may improve the selection of high-risk individuals for LC screening when compared with generalised eligibility criteria which only consider smoking history and age. No currently used RPM integrates genetic risk factors into its calculation of risk. This review provides an overview of the evidence for LC screening, screening related harms and the use of RPMs in screening cohort selection. It gives a synopsis of the known genetic risk factors for lung cancer, and discusses the evidence for including them in RPMs, focussing in particular on the use of polygenic risk scores to increase the accuracy of targeted lung cancer screening.

AB - Lung cancer (LC) is the most common global cancer. An individual’s risk of developing LC is mediated by an array of factors, including family history of the disease. Considerable research into genetic risk factors for LC has taken place in recent years, with both low and high-penetrance variants implicated in increasing or decreasing a person’s risk of the disease. LC is the leading cause of cancer death worldwide; poor survival is driven by late onset of non-specific symptoms, resulting in late-stage diagnoses. Evidence for the efficacy of screening in detecting cancer earlier, thereby reducing lung-cancer specific mortality, is now well established. To ensure the cost-effectiveness of a screening programme, and to limit the potential harms to participants, a risk threshold for screening eligibility is required. Risk prediction models (RPM), which provide an individual’s personal risk of LC over a particular period based on a large number of risk factors, may improve the selection of high-risk individuals for LC screening when compared with generalised eligibility criteria which only consider smoking history and age. No currently used RPM integrates genetic risk factors into its calculation of risk. This review provides an overview of the evidence for LC screening, screening related harms and the use of RPMs in screening cohort selection. It gives a synopsis of the known genetic risk factors for lung cancer, and discusses the evidence for including them in RPMs, focussing in particular on the use of polygenic risk scores to increase the accuracy of targeted lung cancer screening.

U2 - http://dx.doi.org/10.1136/jmedgenet-2020-107399

DO - http://dx.doi.org/10.1136/jmedgenet-2020-107399

M3 - Article

JO - Journal of Medical Genetics

JF - Journal of Medical Genetics

SN - 1468-6244

M1 - 107399

ER -